Job Description

How to Apply

UNIVERSITY OF MICHIGAN SCHOOL OF INFORMATION (UMSI)
WINTER 2025 GRADUATE STUDENT INSTRUCTOR POSITION(S) AVAILABLE
AVAILABLE JOB POSTING: FOR A U-M GRADUATE STUDENT

SIADS 644 - Reinforcement Learning Algorithms
COURSE DATES: 04/01/2025 - 04/28/2025

The School of Information has up to 1 position at .25 fraction, pending enrollment, open for applications. 

Positions reserved as part of funding package: 0

Applications received Winter 2024: n/a

A .25 fraction GSI position offers a monthly stipend, tuition waiver, and health insurance. This appointment runs from January 1, 2025 to April 30, 2025 (from an employment/health benefit perspective).  The course takes place from 4/01/2025 - 4/28/2025. There will be work before and after the course dates. The expected work commitment is roughly 20 hours per week during this time period (roughly 8 weeks). This workload effort is condensed into the described time period mentioned above but your salary is spread across the entire term.  Thus, you will receive a stipend at the end of each month during the semester (January - April).  All of the work hour details will be spelled out in the fraction calculation form for the person hired for this position.

Please indicate your interest by submitting a cover letter and resume electronically using the careers.umich.edu website. Below are some instructions to help you through this application process.

1.       Go to http://www.umjobs.org

2.       Click on "Login"  (upper right corner).  Use your umich uniqname and password.

3.       Click on "U-M Graduate Student on the Ann Arbor campus" identifying yourself as a UM Graduate Student (fourth option)

4.       Click in the "Search for Jobs" box at the top of the page

5.       Enter the Job Opening ID # 256718

6.       You are now in the standard application. Answer all questions and proceed through the application process as prompted.  Upload your application as one document (preferably a Word or PDF document) including your cover letter with information on availability, your resume, and any teaching evaluations*

7.       Click "Submit" when you are finished.

*Having trouble uploading your document? 

The most common cause of upload and display issues can be attributed to an unsupported operating system or internet browser. Internet Explorer is the browser of choice when using the site, however, if one browser doesn't seem to be working properly, switch to a different browser and/or clear your cache and cookies.

Double check your document type. The system accepts resumes/cover letters created in a .DOC, .DOCX, .PDF, .TXT .HTML or .RTF. Uploading your resume/cover letter as a Microsoft Word document is the recommended format. File names are limited to 35 characters or less and cannot contain punctuation marks or special characters.

Course Description

Reinforcement Learning Algorithms --- This course covers the basic principles of reinforcement learning and popular modern reinforcement learning algorithms. Students will develop familiarity with both model-based and model-free reinforcement learning algorithms, including Q-learning, Actor-Critic algorithms, and multi-armed bandit algorithms.

More information about these courses can be found on U-M's Course Catalog via Wolverine Access.

Responsibilities*

Assist in the delivery of UMSI courses on Coursera, grading, holding online office hours, attend weekly staff meetings, managing autograders, answering student questions and communicating clearly with students, and facilitating small group online discussions and student conversations. Demonstrate respect for students as individuals and foster a respectful atmosphere in the online learning environment. This position will also be expected to work collaboratively with lead instructors and other instructional team members.

Required Qualifications*

Graduate student in good standing; 

Must meet eligibility criteria as defined in the GEO contract;

Must be lawfully able to be employed in the United States. Sponsorship to obtain such status is not available at this time;

The applicant must have one or more of the following skill sets:

1.       Programming: proficiency in Python; Jupyter Notebooks; PyTorch, OpenAI.Gym
2.       Mathematics: linear algebra, probability and statistics, dynamic programming, reinforcement learning theory and deep reinforcement learning algorithms . 
3.       Experiment Design: Familiar with implementation of deep reinforcement learning algorithms, including DQN, DDQN, DDPG, SAC. Familiar with the OpenAI.Gym environment. 

Desired Qualifications*

Experience or interest in teaching; 
Strong communication and analytical skills; 
Experience teaching programming and technology skills to beginning students. 

Background Screening

The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third party administrator to conduct background checks.  Background checks are performed in compliance with the Fair Credit Reporting Act.

Contact Information

Please do not contact the faculty member who is teaching the course. Any questions should be directed to [email protected]. 

Decision Making Process

The application due date is November 25th, 2024. All applications will be submitted for review to the faculty member teaching the course. After review of applications and possible interviews, decisions will be made by the faculty member teaching the course.  It is anticipated that decisions will be made by late December.
 

Selection Process

Relevant preparation for teaching the course material; 
Extent of prior instructional/work experience relevant to the course and relevant to the GSI requirements for this course; 
Demonstration of explanatory skills; 
Position?s relevance to graduate training; 
Previous student evaluations, if applicable; 
Availability for course time requirements.

GEO Contract Information

The University will not discriminate against any applicant for employment because of race, creed, color, religion, national origin, ancestry, genetic information, marital status, familial status, parental status or pregnancy status, sex, gender identity or expression (whether actual or perceived), sexual orientation, age, height, weight, disability, citizenship status, veteran status, HIV antibody status, political belief, membership in any social or political organization, participation in a grievance or complaint whether formal or informal, medical conditions including those related to pregnancy, childbirth and breastfeeding, arrest record, or any other factor where the item in question will not interfere with job performance and where the employee is otherwise qualified. The University of Michigan agrees to abide by the protections afforded employees with disabilities as outlined in the rules and regulations which implement Section 504 of the Rehabilitation Act of 1973 and the Americans with Disabilities Act.

Information for the Office for Institutional Equity may be found at https://oie.umich.edu/ and for the University Ombuds at https://ombuds.umich.edu/

Unsuccessful applications will be retained for consideration in the event that there are last minute openings for available positions. In the event that an employee does not receive their preferred assignment, they can request a written explanation or an in-person interview with the hiring agents(s) to be scheduled at a mutually agreed upon time.

This position, as posted, is subject to a collective bargaining agreement between the Regents of the University of Michigan and the Graduate Employees' Organization, American Federation of Teachers, AFL-CIO 3550.

Standard Practice Guide 601.38, Required Disclosure of Felony Charges and/or Felony Convictions applies to all Graduate Student Assistants (GSAs). SPG 601.38 may be accessed online at https://spg.umich.edu/policy/601.38 , and its relation to your employment can be found in MOU 10 of your employment contract.

U-M EEO/AA Statement

The University of Michigan is an equal opportunity/affirmative action employer.

*Please mention you saw this ad on DiversityInCommunityColleges.*

Apply Now