Jobs Mailing List
The Computer Science Department maintains a moderated Jobs Mailing List. The list is open to anyone, students, alumni and even the public at large, who wishes to receive email job postings. The jobs are typically full-time salaried positions for those who have graduated, but can include contract work or other similar opportunities for industry professionals. This list is moderated to eliminate spam. If you'd like to join or post to the Jobs List, please click on the link on the right.
Open Faculty and Staff Positions
- Computer Science Assistant Teaching Professor (Instructor)
- Cybersecurity Tenure Track Faculty Position
Every semester, the Department of Computer Science hires lecturers to teach a variety of classes to our students. These courses encompass a wide range of topics including (but not limited to): programing, data structures, algorithms, database systems, operating systems, software engineering methods and tools, data mining, information visualization, cybersecurity, and network systems.
Needs for courses vary on a semester-by-semester basis; if you are interested in teaching for the department we encourage you to contact us with information on your areas of specialization. The title of Lecturer is given to individuals hired to teach on a course-by-course basis.
The lecturer title may also be granted to a person of high repute in a field of endeavor related to an academic discipline who has been invited by the University to give a series of lectures or otherwise render instruction. Lecturers must have a graduate degree and/or advanced experience in their field of expertise that provides them with the qualifications to teach the particular course or courses they are hired for. Compensation ranges from $7,000 to $12,500 per course, depending on the teaching assignment and qualifications.
Lecturer faculty with 50% appointments or greater are eligible for benefits with the exception of retirement benefits; however, not eligible for leave as outlined on the Benefit Eligibility Matrix. Lecturer positions are not permanent employees and are hired on a temporary basis to teach one or more courses per term. This position is eligible for employee sick leave, earned monthly, on a prorated basis. Lecturers are employees at will and not eligible for tenure. For more information, and to review open opportunities for permanent faculty positions, please visit CU Boulder Jobs.
If you have questions about, or are interested in working with us as a Lecturer in the Department of Computer Science please contact Jessica Lee for information about available opportunities.
Student/Alumni Jobs
Course Support Positions for Undergraduates and Graduate Students
We provide various types of support for our classes, including Course Managers, undergraduate Course Assistants, Undergraduate Teaching Assistants, Graders and Post-Baccalaureate Student Assistants. These programs provide opportunities for undergrad and grads to assist their peers as they pursue the study of computer science.
Job responsibilities
Course Managers provide assistance in managing the following: TAs' logistical support (booking rooms, updating Canvas page, answering students' emails), streamline the duties of graders and CAs, dealing with disability accommodation requests, and other logistical issues associated with large classes. Help faculty with creating quizzes, assignments, rubrics and solutions to assignments/quizzes. CM can occasionally grade or handle regrade requests and often they hold office hours. CMs are expected to hold more managerial and instructional support roles. CMs are not expected to host recitations, exam review sessions, or guest lecture.
Pay
$25 per hour
Skillsets Needed
- Proficiency with C++ and Python programming languages
- Experience designing, implementing, testing, and debugging programs using a high-level programming language and related tools
- Experience with version control, archives, and other tools that manage source code
- Knowledge and experience with software engineering techniques
- Knowledge and experience with data structures and algorithms
- Knowledge and experience with learning management systems, discussion forums, video conference software, and other course support tools
- Good written and oral communication skills
- Ability to work in a team, sometimes remotely
- Good organizational skills. Proactive
- Flexible, patient, creative
- Resourcefulness!
- Positive attitude
- Eager to continue to learn and improve
- Enthusiasm towards the topic taught. Brings passion into the classroom and at office hours.
- Interpersonal skills; desires to build good working relationships with students and team members alike
- Ability to encourage a growth mindset in our students; rather than finding errors/issues in the students' solutions and fixing them, practice ways to encourage the students to find and fix the errors, and arrive at the correct solution on their own.
Eligibility Requirements
Applicants must be currently enrolled in CS graduate degree programs.
How to apply
Please fill out the application form online. You must be logged into Google Suite with your CU credentials to complete this form. See the OIT Google Suite page for help.
Application Deadlines
Fall, Spring and Summer semester opportunities are available.
- For Fall term priority will be given to those who apply by the first Monday of August.
- For Spring term priority will be given to those who apply the third Monday of November.
- For Summer term priority will be given to those who apply by the third Monday of February.
Job responsibilities
Undergraduate Teaching Assistants support specific courses including hosting recitations or workgroups, as well as providing office hours and other support. These positions involve greater direct classroom instructional duties and responsibility for pedagogical materials and plans. UTAs are selected by and report to the instructor(s) of the course. The exact number of positions and selection of courses is subject to change according to the needs of the semester.
In Fall 2022, the Department is seeking UTAs for: CSCI 2824 Discrete Structures. We are considering UTAs for additional courses as resourses allow, though this is not yet confirmed. Apply if interested.
Time commitment
Generally around 10 hours per week for the duration of the term.
Pay
$15 per hour.
Skillsets Needed
- Proficiency with C++ and Python programming languages
- Experience designing, implementing, testing, and debugging programs using a high-level programming language and related tools
- Experience with version control, archives, and other tools that manage source code
- Knowledge and experience with discrete structures, data structures and algorithms
- Knowledge and experience with learning management systems, discussion forums, video conference software, and other course support tools
- Good written and oral communication skills
- Ability to work in a team, sometimes remotely
- Good organizational skills. Proactive
- Flexible, patient, creative
- Resourcefulness!
- Positive attitude
- Eager to continue to learn and improve
- Enthusiasm towards the topic taught. Brings passion into the classroom and at office hours.
- Interpersonal skills; desires to build good working relationships with students and team members alike
- Ability to encourage a growth mindset in our students; rather than finding errors/issues in the students' solutions and fixing them, practice ways to encourage the students to find and fix the errors, and arrive at the correct solution on their own.
For holding recitations and workgroup:
- Interpersonal skills; desires to build good working relationships with students and team members alike
- Ability to work with a group of students
- Ability to spot and deal with challenging behavior
- Resourcefulness! Ability to find resources and solutions for students' questions
- Enthusiasm towards the topic taught. Brings passion into the classroom and at office hours.
Eligibility Requirements
- Undergraduate Teaching Assistants must have had Learning Assistant pedagogical training or equivalent.
- Applicants must be currently enrolled in CU Boulder undergraduate degree programs.
How to apply
To apply, please complete the online application form. You must be logged into Google Suite with your CU credentials to complete this form. See the OIT Google Suite page for help.
Application Deadlines
Fall and Spring semester opportunities are available.
- Applications for Spring 2022 are now open.
- Undergraduate Teaching Assistant positions are filled on a rolling basis.
Job responsibilities
Undergraduate Course Assistants (CAs) support the students and instructors of a specific course. A CA's primary role is to hold office hours to provide support for students who have questions about course material. CAs can also assist with projects assigned by the instructor, be asked to attend course planning meetings, host review sessions, provide basic technical assistance to students of the course, and assist students during lab or recitation sections. This position does no grading and no direct classroom instruction. CAs are supervised by the Manager of the Computer Science Course Assistant Program.
The classes supported by Course Assistants are listed below. Note that not all courses are offered each term, and some courses may not hire CAs for every term offered. Students apply to the CA Program and may list their top three course choices on their application. The CA selection committee may offer applicants any of their top three choices depending on department need.
- CSCI 1000 Computer Science as a Field of Work and Study
- CSCI 1200 Introduction to Computational Thinking
- CSCI 1300 Starting Computing
- CSCI 2270 Data Structures
- CSCI 2275 Programming and Data Structures
- CSCI 2400 Computer Systems
- CSCI 2820 Linear Algebra with Computer Science Applications
- CSCI 2824 Discrete Structures
- CSCI 3010 Programming Project Workshop
- CSCI 3022 Introduction to Data Science with Probability and Statistics
- CSCI 3104 Algorithms
- CSCI 3155 Principles of Programming Languages
- CSCI 3202 Introduction to Artificial Intelligence
- CSCI 3287 Design & Analysis of Data Systems
- CSCI 3308 Software Development Methods & Tools
- CSCI 3753 Design & Analysis of Operating Systems
- CSCI 4622 Machine Learning
Time commitment
Generally 6 to 10 hours per week for the duration of the term.
Pay
$15 per hour.
Eligibility Requirements
- CAs must have taken the course they support (or close equivalent) with a B or better.
- Applicants must be currently enrolled in CU Boulder undergraduate degree programs.
How to apply
Step 1: Complete the online application. You must be logged into Google Suite with your CU credentials to complete this form. See the OIT Google Suite page for help.
Step 2: Submit an unofficial transcript in PDF format to Amy Richards. You can access your unofficial transcript in the BuffPortal.
Step 3: Have a CU Boulder faculty member, instructor, or Computer Science Teaching Assistant submit the recommendation form on your behalf. (If you are applying for both summer and fall, we can use the same recommendation for both applications.) Faculty/Instructors/TAs must be logged into Google Suite with their CU credentials to complete this form. See the OIT Google Suite page for help.
Application Deadlines
Fall, Spring and Summer semester opportunities are available. Application review for each term will continue until all positions have been filled; this can take multiple weeks.
- Applications for summer open March 1 and close April 15.
- Applications for fall open March 1 and close July 15.
- Applications for spring open October 1 and close November 15.
Contact Amy Richards if you have questions about CA positions or the CA application/selection at Amy.L.Richards@Colorado.EDU.
Job responsibilities
Graders mainly grade, support other class staff with grading, manage piazza or communication platforms and provide software support. Create solutions for assignments/quizzes.
Pay
$17 per hour.
Skillsets Needed
- Proficiency with C++ and Python programming languages
- Experience designing, implementing, testing, and debugging programs using a high-level programming language and related tools
- Experience with version control, archives, and other tools that manage source code
- Knowledge and experience with software engineering techniques
- Knowledge and experience with data structures and algorithms
- Knowledge and experience with learning management systems, discussion forums, video conference software, and other course support tools
- Good written and oral communication skills
- Ability to work in a team, sometimes remotely
- Good organizational skills. Proactive
- Flexible, patient, creative
- Resourcefulness!
- Positive attitude
- Eager to continue to learn and improve
- Enthusiasm towards the topic taught. Brings passion into the classroom and at office hours.
- Interpersonal skills; desires to build good working relationships with students and team members alike
- Ability to encourage a growth mindset in our students; rather than finding errors/issues in the students' solutions and fixing them, practice ways to encourage the students to find and fix the errors, and arrive at the correct solution on their own.
Eligibility Requirements
-
Applicants must be currently enrolled in CS graduate degree programs.
How to apply
Please fill out the application form online. You must be logged into Google Suite with your CU credentials to complete this form. See the OIT Google Suite page for help.
Application Deadlines
Fall, Spring and Summer semester opportunities are available.
- For Fall term priority will be given to those who apply by the first Monday of August.
- For Spring term priority will be given to those who apply the third Monday of November.
- For Summer term priority will be given to those who apply by the third Monday of February.
Job Responsibilities
Post-Baccalaureate Student Assistants (SAs) support the students and instructors of a specific course. A SA's primary role is to support the students and instructors of a specific course, or support the Lead Instructor in moderating student communication channels. This includes supporting the course instructor throughout the semester with duties such as grading, providing basic technical assistance to students of the course, and assisting students on the course web forum. This position does no direct classroom instruction.
SAs are supervised by the Program Coordinator of the Computer Science Post-Baccalaureate program.
The classes supported by Student Assistants are listed below. Note that not all courses are offered each term, and some courses may not hire SAs for every term offered. Instructors select the students based on their experience with the material.
- CSPB 1300 Computer Science 1 : Starting Computing
- CSPB 2270 Computer Science 2: Data Structures
- CSPB 2400 Computer Systems
- CSPB 2820 Linear Algebra
- CSPB 2824 Discrete Structures
- CSPB 3022 Introduction to Data Science with Probability and Statistics
- CSPB 3104 Algorithms
- CSPB 3155 Principles of Programming Languages
- CSPB 3202 Introduction to Artificial Intelligence
- CSPB 3287 Design and Analysis of Database Systems
- CSPB 3308 Software Development Methods and Tools
- CSPB 3702 Cognitive Science
- CSPB 4122 Information Visualization
- CSPB 4502 Data Mining
Starting Pay
$18.00 per hour
Eligibility Requirements
- SAs must have taken the course they support (or close equivalent) with a B or better.
- Applicants must be currently enrolled in a Computer Science degree program at CU Boulder.
Role Requirements
- Proficiency with C++ and Python programming languages
- Experience designing, implementing, testing, and debugging programs using a high-level programming language and related tools
- Good written and oral communication skills
- Ability to work in a team, sometimes remotely
- Good organizational skills. Proactive
- Flexible, patient, creative
- Resourcefulness!
- Positive attitude
- Eager to continue to learn and improve
- Enthusiasm towards the topic taught. Brings passion into the classroom and at office hours.
- Interpersonal skills; desires to build good working relationships with students and team members alike
- Ability to encourage a growth mindset in our students; rather than finding errors/issues in the students' solutions and fixing them, practice ways to encourage the students to find and fix the errors, and arrive at the correct solution on their own.
Desired Qualifications:
- Experience with version control, archives, and other tools that manage source code
- Knowledge and experience with software engineering techniques
- Knowledge and experience with data structures and algorithms
- Knowledge and experience with learning management systems, discussion forums, video conference software, and other course support tools
Time Commitment
5 to 20 hours per week for the duration of the term, depending on the needs of the instructor and course.
How to apply
Applications are currently open for the Summer, 2022 semester. The employment term will be from May 16th, 2022 through August 5th, 2022 (unless you are a graduating senior) and applicants must be available for the majority of this time.
If you are interested, please fill out the Summer, 2022 Post-Bacc Student Assistant Application. (Will open new window)
Application Deadlines
Fall, Spring and summer semester opportunities are available. Application review for each term will take place on a rolling basis and continue until all positions have been filled. This can take multiple weeks.
Contact Vanessa Luna if you have questions about SA positions or the SA application/selection.
Job Responsibilities
The Computer Science department at the University of Colorado Boulder is seeking highly qualified students to serve as CSEL Ambassadors. CSEL is the acronym for the CS Education Lab, located in the Computer Science wing of the Engineering Center. As a CSEL Ambassador, you’ll facilitate the operations of the CSEL and foster a positive community for CS majors and other undergraduates taking classes from the Computer Science department. Typical duties for this position include managing access to study rooms, creating a positive working environment, directing students throughout the engineering center, and providing a Computer Science student perspective as needed.
Time Commitment
5-10 hours per week, Must be able to work between the hours of 9 AM to 8 PM, Monday-Friday. Your schedule will be flexible around any class/other commitments that you have. Commitment is for the semester to which you apply, but may be eligible for additional semesters based on job performance.
Pay
$15/hour
Preferred Qualifications
-
Knowledge of the computer science department and the CS undergraduate curriculum
-
Good organizational skills
-
Flexible, patient, creative
-
Positive attitude
-
Good interpersonal skills; desires to build good working relationships with students and team members alike
Eligibility Requirements
- Current undergraduate Computer Science student at CU Boulder
-
Rank: Students must hold a Sophomore rank or higher
-
Minimum 2.80 GPA
-
Students must be in good standing with the university.
-
Able to attend in-person training one week prior to the start of the semester
How to Apply
Complete the online application. Please be aware that you will need to submit an unofficial transcript during the application process to verify you meet the GPA requirement. You must be logged into Google Suite with your CU credentials to complete this form. See the OIT Google Suite page for help.
If you have any questions about the application process, please contact csfrontoffice@colorado.edu.
Application Deadlines
Fall and Spring semester opportunities are available. Application review for each term will continue until all positions have been filled; this can take multiple weeks.
-
For Fall term priority will be given to those who apply by the first Monday of June. Applications will open the first day of registration for Fall Semester.
-
For Spring term priority will be given to those who apply by the first Monday of November. Applications will open the first Monday of October.
Contact
If you have questions about the CSEL Ambassador position or the Ambassador application/selection process please contact csfrontoffice@colorado.edu.
Job Responsibilities
Some of the responsibilities associated with the Networking Lab Assistant role include but are not limited to:
- Introduce and train new lab students into how to interconnect compute, storage and networking equipment for their course deliverables/assignments.
- Supervise that student experiments are executed in a safe and professional matter.
- Document and/or perform compute/network equipment installation and repair.
- Assist Faculty in the setup of lab experiments used for academic instruction.
- Provide ocasional support in revising and grading lab implementations under instructor supervision.
Pay
$15/hr-$20/hr depending on qualifications.
Preferred Qualifications
- Strong understanding of network technologies and protocols
- Ability to install operating systems and applications in bare metal and virtual environments.
- Familiarized with networking cabling installation and troubleshooting.
- Some proficiency in the configuration of networking equipment such as Cisco, Juniper or Arista is required.
- Ability to communicate effectively with groups of people in a professional manner.
- Knowledge about power distribution systems in a computer center environment is desirable.
- Able to lift 40 pounds.
How to apply
Please send your resume and cover letter to neteng@colorado.edu, and indicate you are interested in the Lab Assistant Position.
Job responsibilities
ISS Managers provide assistance in managing the following: TAs' logistical, streamline the duties of TAs, Graders and CMs. Provide training to TAs, CMs and graders. Interview prospective TAs and help the department in creating a TA pool for the department. Coordinate with other campus resources to bring relevant workshops to the ISS community. ISS Managers are expected to hold more managerial and instructional support roles. Other course support duties, as assigned.
Pay
$25 per hour
Skillsets Needed
- Leadership skills
- Proficiency with C++ and Python programming languages
- Experience designing, implementing, testing, and debugging programs using a high-level programming language and related tools
- Experience with version control, archives, and other tools that manage source code
- Knowledge and experience with software engineering techniques
- Knowledge and experience with data structures and algorithms
- Knowledge and experience with learning management systems, discussion forums, video conference software, and other course support tools
- Good written and oral communication skills
- Ability to work in a team, sometimes remotely
- Good organizational skills. Proactive
- Flexible, patient, creative
- Resourcefulness!
- Positive attitude
- Eager to continue to learn and improve
- Enthusiasm towards the topic taught. Brings passion into the classroom and at office hours.
- Interpersonal skills; desires to build good working relationships with students and team members alike
- Ability to encourage a growth mindset in our students; rather than finding errors/issues in the students' solutions and fixing them, practice ways to encourage the students to find and fix the errors, and arrive at the correct solution on their own.
Eligibility Requirements
Applicants must be currently enrolled in CS graduate degree programs and selected as one of the Lead TAs of the Department.
How to apply
Please fill out the application form online. You must be logged into Google Suite with your CU credentials to complete this form. See the OIT Google Suite page for help.
Application Deadlines
Fall, Spring and Summer semester opportunities are available.
- For Fall term priority will be given to those who apply by the first Monday of August.
- For Spring term priority will be given to those who apply the third Monday of November.
- For Summer term priority will be given to those who apply by the third Monday of February.
Job responsibilities
Graders mainly grade, support other class staff with grading, manage piazza or communication platforms and provide software support. Create solutions for assignments/quizzes.
Pay
$15 per hour.
Skillsets Needed
- Proficiency with the C and BASH programming languages, and the Linux Operating System
- Experience designing, implementing, testing, and debugging programs using a high-level programming language and related tools
- Experience with version control (Git), archives, and other tools that manage source code
- Knowledge and experience with software engineering techniques and modular C programming
- Knowledge and experience with data structures, algorithms and the Linux Kernel
- Knowledge and experience with learning management systems (Canvas and Moodle), discussion forums (Piazza and Discord), video conference software (Zoom), and other course support tools
- Good written and oral communication skills
- Ability to work in a team, sometimes remotely
- Good organizational skills. Proactive
- Flexible, patient, creative
- Resourcefulness!
- Positive attitude
- Eager to continue to learn and improve
- Enthusiasm towards the topic taught. Brings passion into the classroom and at office hours.
- Interpersonal skills; desires to build good working relationships with students and team members alike
- Ability to encourage a growth mindset in our students; rather than finding errors/issues in the students' solutions and fixing them, practice ways to encourage the students to find and fix the errors, and arrive at the correct solution on their own.
Eligibility Requirements
- Applicants must be currently enrolled in CS degree programs.
How to apply
Please fill out the application form online. You must be logged into Google Suite with your CU credentials to complete this form. See the OIT Google Suite page for help.
Research Opportunities for Undergraduate and Graduate Students
Many of the projects at CLEAR rely on human annotators for creating training data for machine learning systems. At the beginning of every semester, we hire one or two students for these positions. These students tend to be linguistics students, but some of our best annotators have also come from other departments like CS or Philosophy. The positions are all student hourly and include sick leave accrual. The following types of annotator positions are typically available:
Someone with no prior annotation experience, but with an eye for detail, good work habits, the ability to work independently and a love of language. Duties would be expected to begin with simple multi-class annotation such as word sense tagging or Named Entity tagging (don’t worry if you’re not familiar with these terms).
Usually an undergraduate student, Student Assistant 1
Pay: $15-17
Someone with a demonstrated track record of successful, high quality annotation who can stay on task and focused and enjoys the varied data they encounter. Duties would be expected to encompass more challenging annotation such as coreference or temporal relations, on different domains and perhaps different languages.
Usually a senior or a new graduate student, Student Assistant 2,
pay range $16-$18
someone with an exemplary track record in challenging annotation tasks who has the self-discipline and motivation to take on the management of an annotation project and multiple annotators, including annotator training, adjudication and revision of guidelines.
Usually a graduate student, Student Assistant 3,
pay range $17-19
Someone with experience with annotation projects and strong computational skills who can provide support for annotation tools and data processing for multiple projects.
Usually a CS graduate student, Student Assistant 3,
pay range $17-19
Someone with attested research skills and enthusiasm and motivation for the topic at hand who can devise new approaches and methodologies for independent research in the areas of Lexical Semantics & Resources, Ontology development and Semantic processing.
Usually a PhD student, Student Assistant 4,
pay range $18-$25
If you interested in any of these part-time hourly positions, please contact Martha.Palmer@colorado.edu or kristin.wrightbettner@colorado.edu
Job Description
Research and project management for the NSF SWIFT Passive and Active Spectrum Sharing research project
Job Responsibilities
- Work with the RF baseline noise survey team to conduct RF noise surveys
- Assist the project PI with project management and activities coordination
Requirements
- Must have a senior class standing
- Must be flexible and adaptable to changing requirements and priorities
- Excellent communication skills to keep team informed of project status and progress
- Familiarity with Agile Project Management frameworks and principles
- Excellent organization skills
Time commitment
15-20 hours per week.
Pay
$24.00 per hour
Eligibility Requirements
Applicants must be currently enrolled in CU Boulder undergraduate degree programs.
How to apply
Please email Kevin Gifford a cover letter and up-to-date resume.
Application Deadline
September 1, 2021
Job Description
Graduate Researcher (hourly) and project management for the NSF SWIFT Passive and Active Spectrum Sharing research project
Job Responsibilities
- Work with the RF baseline noise survey team to conduct RF noise surveys
- Assist the project PI with project management and activities coordination
Requirements
- Must be flexible and adaptable to changing requirements and priorities
- Excellent communication skills to keep team informed of project status and progress
- Familiarity with Agile Project Management frameworks and principles
- Excellent organization skills
Time commitment
15-20 hours per week.
Pay
$20.00 per hour
Eligibility Requirements
Applicants must be currently enrolled in a CU Boulder Graduate degree program.
How to apply
Please email Kevin Gifford a cover letter and up-to-date resume.
Application Deadline
December 15, 2021
Job Description
Graduate Researcher (hourly) for the NSF SWIFT Passive and Active Spectrum Sharing research project. Emphasis is upon wireless communications and open-source 3GPP LTE and 5G.
Job Responsibilities
- Research, evaluate and prototype current open-source implementations of the 3GPP mobile cellular communications architecture for research support
Requirements
- Must have, or be currently enrolled in, wireless communications experience/coursework
- Must have previous LTE or 5G work experience
- Must have software development experience
- Must be flexible and adaptable to changing requirements and priorities
- Excellent communication skills to keep team informed of project status and progress
- Familiarity with Agile Project Management frameworks and principles
- Excellent organization skills
Time commitment
10-12 hours
Pay
$20 - $25/hour
Eligibility Requirements
Applicants must be currently enrolled in a CU Boulder Graduate degree program.
How to apply
Please email Kevin Gifford a cover letter and up-to-date resume.
Application Deadline
December 15, 2021
Job Description
Undergraduate Research Assistant
Job Responsibilities
Conduct interviews with cheer coaches and instructors and, in collaboration with the research team, qualitatively code the interviews
- Attend and observe cheer practices and events and take field notes.
- Make sketches of wearable technologies and tools that might be useful based on synthesis of interviews and practice observations.
- Produce high fidelity prototypes of new wearable technologies and tools
- Assist with the development of computing and statistics curricula around cheerleading and dance.
- Assist with the planning and execution of studies with cheer and dance teams, including taking field notes, helping athletes to use technologies, audio and video recording, and analysis of data collected.
Requirements
- Junior or Senior in Engineering
- 2+ years of experience as a cheerleader or dancer
- Prior experience programming and creating wearables
- Prior experience participating in educational research projects
Time Commitment
Up to 20 hours per week.
Pay
$18 per hour
How to apply
Email abzi3734@colorado.edu with your resume and a few sentences explaining your interest in the job
Application Deadline
Wednesday, December 1, 2021
Student Assistants
- Student Assistant: Undergraduate student web developer
- Student Assistant: Designing for Defense (PACAF D4D)
- Student Assistant: Designing for Defense (NSA D4D)
- Student Assistant: Front Office Assistant
- Student Assistant: Designing for Defense (USASMDC D4D)
- Student Assistant: Designing for Defense (SPACECOM D4D)
Job Description
Create a webpage for the CU-Boulder Passive and Active Spectrum Sharing (“CU PASS”) NSF Project and for the CU-Boulder Wireless Interdisciplinary Research Group.
Job Responsibilities
- Create and maintain a CU Boulder website for CU PASS Project and the IWRG research group
- Ensure the website meets CU-Boulder College of Engineering guidelines
Requirements
- Must have a junior or senior class standing
- Must be flexible and adaptable to changing requirements and priorities
- Excellent communication skills to keep team informed of project status and progress
- Familiarity with WebExpress as a website framework
- Excellent organization skills
Time commitment
15-20 hours per week.
Pay
$16.00 per hour
Eligibility Requirements
Applicants must be currently enrolled in CU Boulder undergraduate degree programs.
How to apply
Please email Kevin Gifford a cover letter and up-to-date resume.
Application Deadline
May 22, 2021
Project Name
D4D PACAF Team Project
Project Background
- CHALLENGE: Pacific Air Forces logistics managers need an effective way to conduct cost-benefit analysis for potential logistics solutions in order to execute successful logistics maneuvers across the Indo-Pacific.
- RELEVANT CONTEXT:
- PACAF operates in environments spanning vast spaces with few landmasses and carries out maneuvers such as moving people and materiel across island chains, providing logistics support for sorties, and providing power to rapidly-assembled structures.
- PACAF relies on a concept called Agile Combat Employment (ACE) to provide decentralized logistics solutions that can disperse, recover, and resume operations in contested environments.
- Logistics managers leverage ACE to manage PACAF’s sprawling logistics network, but the concept does not provide tools to analyze the cost-benefit of investing in different solutions.
- Planners would like to determine optimal solutions for managing logistics problems – commercial solutions, designing technologies in-house, “Swiss Army Knife” solutions, etc.
- IMPACT: Developing a solution that will allow logistics managers to evaluate different available solutions, specifically for fuel support and runway repair. The Air Force needs to adapt its equipment and deliverable capabilities to match the ACE doctrine in order to effectively operate in the Pacific.
Project Description
The needs for our project can be broken down into four segments.
- Data Cleaning and Organization: Through the semester, our team has collected datasets from two main sources. The first of which is a “cadillac” list of all available fuel and runway repair materials that the Air Force could deploy to ACE bases in the event of a conflict. It contains information about equipment cost, size, and weight. Our other data set consists of available runway locations and their respective infrastructure, offensive, and defensive capabilities.
Goal: Our team needs help collecting, cleaning, and distilling our data into a usable database (~10% of work, to be completed by the end of March).
- Optimization: The thinking behind ACE is to disperse Air Force capabilities and maintain agility without sacrificing combat capability. The proposed strategy would establish small bases in austere island environments that operate for short time periods. Given these geographical, chronological, and logistical constraints, our goal is to optimize the amount and type of materials from the cadillac list that would be sent to each base. These requirements will change based on the mission and other requirements.
Goal: Develop optimization/cost-benefit analysis tool for analyzing equipment loadouts in changing environments (~50% of work, to be completed early to mid April).
- As our goal is to provide the structure of a usable tool for the Air Force, we would like to design a basic UI for accessing and visualizing this data. Furthermore, our team could use help adding more functionality and visuals to our existing website, although this need is secondary to our main goal of developing the tool.
Goal: Build basic UI for the operation of said tool that can find the optimal equipment output given a set of variables and constraints. Have a minimum viable product for delivery to sponsors. (~30% of work, to be completed by mid to late April).
- We are currently constrained to using unclassified data. Eventually, we would like to incorporate our tool into existing Air Force data and logistics management systems. In the short-run, that means building from a “sandbox” scenario to map out the most effective bases and what materials/equipment should be deployed to each one.
Goal: Conduct several case study scenarios within the tool to work into our strategic proposal report. Eventually collect and build in larger amounts of data (~10% of work, to be completed by late April, with the possibility of extension into summer term).
Project Duration
Through the end of the semester (~7 weeks), but could be slightly longer or shorter depending on needs of the project.
Number of Hours
Our team will need outside support in the range of 10 to 15 hours per week. We are open to dividing this work among multiple students from the CS department.
Technical Skills Required
- Data Cleaning and Organization
- Linear Programming and Optimization
- Predictive Analytics
- Database Management
Other Desired Skills
- Network Integration
- Basic UI Design
- Website Design
Pay Rate
The position will pay $20 per hour.
The hired individual will turn in the number of hours worked each week to the D4D PACAF student team for review. Upon their approval it will be sent to the course instructor (Andrew Meyer) for final approval.
How to Apply
Qualified candidates should send their resume along with a brief letter describing their qualifications to Andrew Meyer at meyerandy1228@msn.com.
Project Name
National Security Agency (NSA) D4D Project.
Project Background
NSA researchers need to identify and analyze foreign disinformation campaigns in order to inform cybersecurity priorities.
Project Description
- Detecting foreign misinformation is a large and technically challenging undertaking. Data scientists need to determine if they can even identify the degree of "foreignness" related to online information and then diagnose if the information is false or not. Identifying the source of disinformation can improve U.S. counter-disinformation operations.
- The NSA has launched campaigns to identify disinformation stemming from specific adversarial entities. Now, the NSA needs to determine if open source-driven analysis on platforms leveraged by foreign entities for these disinformation campaigns is possible.
- The NSA is even interested in understanding if open source analysis on platforms used most often by foreign entities for disinformation campaigns is not possible. If it is not possible, the government can proceed with other, more useful counter-disinformation operations.
The D4D student team is looking for technical help that can assist them with coding their potential solutions.
Project Duration
A maximum of 8 weeks (Subject to change.) It may be less than 8 weeks or a little longer].
Number of Hours
The expected amount of time required for this position is approximately 5 – 10 hours per week. The D4D student team also requires that the applicant be able to meet with the team once a week for approximately 1 hour over Zoom. The applicant must possess strong communication skills.
Technical Skills Required
- Strong Python and JavaScript Skills
- Experience with Machine Learning
- Experience with Natural Language Processing (NLP)
- Experience with Graph Algorithms / Graph Theory
- Experience with Robotic Process Automation (RPA)
- Experience with Selenium
Other Desired Skills
- Experience with Linear / Integer Programming
- Experience with Investigating Domain Ownership
- Graduate Student
Pay Rate
The position will pay $20 per hour.
The hired individual will turn in the number of hours worked each week to the D4D NSA student team for review. Upon their approval it will be sent to the course instructor (Andrew Meyer) for final approval.
How to Apply
Qualified candidates should send their resume along with a brief letter describing their qualifications to Andrew Meyer at meyerandy1228@msn.com. Be certain to mention that you are specifically applying for the position working with the D4D NSA student team.
Job Responsibilities
The Computer Science department at the University of Colorado Boulder is seeking highly qualified students to serve as Front Office Assistant. Students will work in the Computer Science Department Main Office in ECOT 717 assisting with general office duties, including accepting and sorting mail, answering phones, giving directions, booking rooms and other tasks as assigned.
Time Commitment
5-10 hours per week, Must be able to work between the hours of 9 AM to 5 PM, Wednesday and Friday. Your schedule will be flexible around any class/other commitments that you have. Commitment is for the remainder of Spring 2022 Semester.
Pay
$15/hour
Preferred Qualifications
-
Knowledge of the computer science department
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Good organizational skills
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Flexible, patient, creative
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Positive attitude
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Good interpersonal skills; desires to build good working relationships with students and team members alike
Eligibility Requirements
-
Current undergraduate Computer Science student at CU Boulder
-
Rank: Students must hold a Sophomore rank or higher
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Minimum 2.80 GPA
-
Students must be in good standing with the university.
-
Training will be on your first day of work.
How to Apply
Complete the online application. Please be aware that you will need to submit an unofficial transcript during the application process to verify you meet the GPA requirement. You must be logged into Google Suite with your CU credentials to complete this form. See the OIT Google Suite page for help.
If you have any questions about the application process, please contact csfrontoffice@colorado.edu.
Application Deadlines
Applications will be open until the position is filled. Applications submitted by March 14th will be given priority.
Contact
If you have questions about the Front Office Assistant position or the application/selection process please contact csfrontoffice@colorado.edu.
Project Name
US Army Space Missile Defense Command (USASMDC) D4D Project.
Project Background
USASMDC ground station operators need a way to efficiently evaluate anomalies identified in their mesh satellite network in order to better manage and secure it from threats and system failures.
Project Description
- Practical experience with applying Machine learning (Supervised & Unsupervised learning algorithms) to datasets related to any domain (preferably satellite systems data)
- Be able to extract features, suggest and apply models on large datasets and interpret results for a non-technical audience.
- ML Programming experience using R/Python/Matlab
The D4D student team is looking for technical help that can assist them with coding their potential solutions. Specifically, the candidate will help the team with data reprocessing/cleaning, extracting useful features, training data on models and interpreting the results to achieve the end goal of anomaly detection and classification project
Project Duration
A maximum of 8 weeks (Subject to change.) It may be less than 8 weeks or a little longer].
Number of Hours
The expected amount of time required for this position is approximately 10 – 20 hours per week. The D4D student team also requires that the applicant be able to meet with the team once a week for approximately 1 hour over Zoom. The applicant must possess strong communication skills.
Technical Skills Required
The candidate will help the team with data preprocessing/cleaning, extracting useful features, training data on models and interpreting the results to achieve the end goal of anomaly detection and classification project.
Pay Rate
The position will pay $20 per hour.
The hired individual will turn in the number of hours worked each week to the D4D NSA student team for review. Upon their approval it will be sent to the course instructor (Andrew Meyer) for final approval.
How to Apply
Qualified candidates should send their resume along with a brief letter describing their qualifications to Andrew Meyer at meyerandy1228@msn.com. Be certain to mention that you are specifically applying for the position working with the D4D USASMDC student team.
Project Name
D4D SPACECOM Team Project
Project Background
Sponsoring Organization
US Space Command (USSPACECOM)
Challenge
USSPACECOM leaders/decision makers need to be able to accurately determine the intent of others’ actions.
Relevant Context
- Due to the uncertainty of human psychology, determining intent of actions is very difficult.
- Due to the myriad entities involved in the Space Enterprise (e.g., commercial, civil, military), dual use technology, and the great observational distances involved, it is possibly more difficult to determine intent of actions in space than in other domains. It is thus extremely difficult to determine appropriate responses to these actions.
- USSPACECOM is interested in examining how hostile intent has been/is determined for other domains and what systems and/or processes might be incorporated/changed to improve the accuracy and timeliness of determining hostile intent for space operations.
Project Description
The project you would be working on is a data aggregation system that pulls satellite positioning data (Radar, TLE sets, etc.) from disparate public databases and deposits them into an SAP HANA database. These various data sources would be polled regularly and queue work to HANA compute clusters which will handle various processing/data fusion tasks.
Built on top of this system would be various analytics systems designed to detect significant changes in data/ suspicious satellite behavior.
The D4D student team is looking for technical help that can assist them with coding their potential solutions. Specifically, the candidate will help the team with data reprocessing/cleaning, extracting useful features, training data on models and interpreting the results to achieve the end goal of anomaly detection and classification project
Project Duration
A maximum of 8 weeks (Subject to change.) It may be less than 8 weeks or a little longer].
Number of Hours
The expected amount of time required for this position is approximately 5 – 15 hours per week (this is flexible)
Technical Skills Required
A combination of these skills will be required.
- Firm understanding of various object oriented programming languages (java, python, C++ etc)
- Cloud computing platforms (Google Cloud or AWS)
- Kafka
- Machine Learning
- Data Analytics
- Database systems (SQL/ NOSQL)
- SAP HANA (preferred but not necessary)
Other Desired Skills
- Space domain understanding is a plus (not required)
Pay Rate
The position will pay $20 per hour.
How to Apply
Qualified candidates should send their resume along with a brief letter describing their qualifications to Andrew Meyer at meyerandy1228@msn.com. Be certain to mention that you are specifically applying for the position working with the D4D SPACECOM student team.