Previous Job Postings

University of Michigan

Data Scientist – Predictive Analytics (Michigan Medicine – Ann Arbor, MI) 


Newlab

Program Director (Brooklyn, NY)


Starr Commonwealth

Evaluator Position  (Albion, MI; Remote)


University of Rochester, Goergen Institute for Data Science

Assistant Professor  (Monroe County, NY)


Walter P Moore

Intern (Houston, TX)


Public Interest Technology

Backend Software Developer (Ann Arbor, MI)


Public Interest Technology

Frontend Software Developer (Ann Arbor, MI)


Spring Matter

Lead Data Scientist (Ann Arbor, MI)


University College London

Lecturer, Data Intensive Science (London, UK)


Ad-iD

Metadata and Taxonomy Specialist

Metadata Team Lead


Midwest Big Data Hub

Science Writing Internship Opportunity (Flexible Location)


University of Michigan

Data Architect Senior (Ann Arbor, MI)


University of Michigan

Data Programmer (Ann Arbor, MI)


Previous Training and Educational Opportunities

University of Michigan, ISR

Capacity Building Teaching Assistant Position


University of Michigan’s School of Information

Postdoc in Innovation


University of Michigan Department of Learning Health Sciences

Research Fellow (Ann Arbor, MI)


U.S. Environmental Protection Agency (EPA)

Postdoctoral Fellowship in Laboratory Systems Data Analysis

Student Research Assistant Positions

For MIDAS Affiliated Faculty:
If you are a faculty member and would like to submit a research project you are looking for student assistance/collaboration on please submit the below form:

Submit Research Project

The following projects are seeking student research assistants (click name to expand):

Health Equity and Vaccine Uptake Personalization

Health Equity and Vaccine Uptake Personalization

Description: “Developing a COVID-19 vaccine is just half the battle – you have to get Americans to take it” (Milkman et al., June 5, 2020, USA Today). Policymakers around the world are embracing behavioral science – that is, integrating behavioral science with an iterative and data-driven approach – to improve societal well-being (The Economist, May 20, 2017). In addition, behavioral science has played a key role in developing simple, scalable strategies that have been proven to increase vaccination rates (e.g., Milkman et al., 2011). An important, and timely, question is: How can these insights be leveraged to effectively increase vaccine uptake not only for the common flu but also for the current Coronavirus disease (COVID-19), especially when a substantial part of the public is vaccine hesitant? What has received minimal attention is the question of what interventions are most likely to increase vaccine uptake among different racial and ethnical groups. This is particularly important because there are significant disparities not only in Americans’ willingness to get vaccinated but also in terms of hospitalization and death rates. For example, minorities have been disproportionately affected both by the current COVID-19 pandemic as well as the common flu, yet they are among the most vaccine hesitant groups (Akintobi et al., 2020; CDC 2020; Romeo and Jordan, 2020). We will leverage data from a “mega-study” on increasing actual flu shot uptake (spearheaded by the Behavioral Change for Good Initiative, BCFG and the Penn Medicine NudgeUnit, PMNU), which reached approximately 1.3 million U.S. adults in flu season 20/21 – the largest study of its kind. Specifically, we plan to apply machine learning (ML) modeling methods to inform targeted and scaled vaccination uptake strategies and contribute to a COVID-19and common flu response aimed at reducing racial and ethnic disparities in vaccination uptake, thereby improving health equity. 

Under the primary mentorship of Dr. Ladhania, the students will be responsible for data analysis – data cleaning; implementing personalization algorithms on the data; analyzing, visualizing, and interpreting the results from the analyses.

Student Research Assistant Responsibilities: If you are a student interested in a paid opportunity to work on a health equity and machine learning project aimed at increasing vaccine uptake during the COVID-19 pandemic with a focus on under-represented minorities, please email Dr. Rahul Ladhania (Assistant Professor, Health Management & Policy and Biostatistics, School of Public Health). This opportunity is available through a Robert Wood Johnson Foundation grant. We have funding to support a multi-university interdisciplinary collaboration among Dr. Rahul Ladhania, Dr. Nina Mazar (Professor, Marketing, Boston University), and Dr. Lyle Ungar (Professor, Computer and Information Science, University of Pennsylvania). The core research team brings together expertise in behavioral science, medicine, and machine learning to accelerate our understanding of how to effectively increase vaccination rates for different populations.

We have funds to help support work from up to 2 graduate students (strong undergraduate senior applicants will also be considered) till January 2022. This work will be compensated at the temp GSRA hourly rate, and the number of hours would vary from 10-20 per week (i.e., this is not a GSRA position).

QualificationsThe ideal applicant should have:

  1. Strong programming skills in a statistical language – e.g., R (preferred), python, Julia
  2. Background and training in causal inference methods
  3. Background in statistical and ML methods – logistic regression, recursive partitioning trees and forests
  4. Creativity, enthusiasm, and good verbal and written communication skills
  5. Strong interest in working on problems in healthcare and machine learning (prior experience is not required)

How to apply: Interested applicants should submit their curriculum vitae, cover letter indicating relevant qualifications and research interests, to Dr. Rahul Ladhania (ladhania@umich.edu), using the subject line “Health Equity Vaccine RA Application”. University of Michigan at Ann Arbor is an equal opportunity/affirmative action employer. The application process may involve a coding exercise to evaluate candidate fit.

Applications Due: ASAP. Open until filled, applications will be reviewed on a rolling basis. 

Contact: Please email Dr. Rahul Ladhania (ladhania@umich.edu) if you have any questions.

Date Posted
7/27/2021

Equitable Modeling for Persistent Opioid Use Prediction & Personalization

Equitable Modeling for Persistent Opioid Use Prediction & Personalization

Description: Oftentimes, datasets used for decision-making, by design or default, do not adequately capture under-represented populations. Inference, predictive or causal, drawn from algorithms trained on these datasets has, at best, limited utility for these populations. At worst, it can lead to decisions with adverse outcomes. These costs are further exacerbated when applied in sensitive domains – 1) crime prediction 2) job hiring decisions and 3) clinical decision-making. In this context, opioid over/misuse, while continuing to be one of the US’ most pressing public health problems also represents a highly stigmatized behavior. Given the highly sensitive nature of this problem, if under-represented populations suffer from higher risks of misclassification, that has strong implications for equity and fairness in public health. In this project, we aim to estimate costs of these modeling ‘inequities’ in the context of predicting persistent opioid use (POU), and adapt machine learning models to address them. To accomplish this we will: (a) quantify the costs of applying three existing models for predicting POU to under-served populations, and (b) adapt transfer learning approaches to generalize predictions to these populations to calibrate a model which is robust to dataset and sub-population shifts, for unbiased identification of at-risk individuals across sub-groups.

Under the primary mentorship of Dr. Ladhania, the student hire will work on a data analysis project for estimating costs of modeling these ‘inequities’ in the context of predicting POU, and adapting machine learning models to address them.

Student Research Assistant Responsibilities: If you are a student interested in a paid opportunity to work on a project on Equitable Modeling for Persistent Opioid Use Prediction & Personalization, please email Dr. Rahul Ladhania or Dr. Anne Fernandez. This opportunity is available through a MIDAS PODS grant. MIDAS PODS at Michigan has generously provided funding to support a collaboration among Dr. Rahul Ladhania (Assistant Professor of Health Management & Policy), Dr. Anne Fernandez (Assistant Professor, Department of Psychiatry), Dr. Karandeep Singh (Assistant Professor, Learning Health Sciences), and Dr. Paramveer Dhillon (Assistant Professor, School of Information).

We have funds to help support work from up to 1 Masters or rising Senior student through the grant till June 2022. This work will be compensated at the temp hourly rate at the level of GSRA hourly rate, and the number of hours would vary from 10-20 per week (i.e., this is not a GSRA position).

QualificationsThe ideal applicant should have:

1. Strong programming skills in a statistical language – e.g., R (preferred), python, Julia

2. Desired (but not required) background in statistical and ML methods – logistic regression, recursive partitioning trees and forests, ensemble methods

3. Creativity, enthusiasm, and good verbal and written communication skills

4. Strong interest in working on problems in healthcare and machine learning (prior experience is not required)

How to apply: Interested applicants should submit their curriculum vitae, cover letter indicating relevant qualifications and research interests, to Dr. Rahul Ladhania (ladhania@umich.edu), using the subject line “Equitable Models for POU RA Application.” University of Michigan at Ann Arbor is an equal opportunity/affirmative action employer. There is no citizenship requirement for this position. The application process may involve a programming exercise to evaluate candidate fit.

Applications Due: Open until filled, applications will be reviewed on a rolling basis

Contact: Please email Dr. Rahul Ladhania (ladhania@umich.edu) or Dr. Anne Fernandez (acfernan@med.umich.edu) if you have any questions.

Date Posted
7/15/2021

Fall GSRA Position Announcement in Computational Social Science Course Development (Bruch, Jacobs, and Romero)

Fall GSRA Position Announcement 

COMPUTATIONAL SOCIAL SCIENCE COURSE DEVELOPMENT

Professors Bruch, Jacobs, and Romero are developing a Computational Social Science class for undergraduate students with little or no programming experience. We are looking for a graduate student to assist us in developing Jupyter notebooks, lectures, and labs that introduce students to basic Python programming and CSS methods for text analysis, network analysis, and machine learning. 

The position will be funded through a GSRA position at 20 hours/week, which will cover tuition and stipend at standard rates. It will run through Fall semester and possibly Winter semester. You will be working closely with the faculty leads, as well as four undergraduate RAs who will be testing the modules, providing input on content, and otherwise assisting with course development. 

Qualifications: We are looking for a graduate student from Computer Science, Information, Data Science, Quantitative Social Science, or some related area with relevant experience with data analysis or computational social science. Experience in Python is required; the ideal candidate would have exposure to tools for doing social network analysis, machine learning, and/or text analysis and a strong interest in computational social science. Enthusiasm for developing innovative, hands-on educational materials is a must. Experience teaching and/or delivering hands-on teaching materials for undergraduate courses is desirable but not required. 

How to apply: Please email your cover letter describing your interest and fit for the position, CV, and a copy of your unofficial transcript to Daniel Romero (drom@umich.edu ) and Elizabeth Bruch (ebruch@umich.edu ). 

Deadline to apply: We will be reviewing applications as they come until the positions are filled.

Date Posted
5/07/2021

Research Assistant (Dr. Emily Fields)

Research Assistant Job Description:

Dates: Starting May or June 2021, 15-20 hours/week for 10 weeks

Salary: $16/hour

 

Description: I am seeking a detail-oriented and proactive student to assist with research activities related to a project on school and neighborhood racial segregation. The Research Assistant will first be tasked with a data cleaning project that will require both secondary research and meticulous attention to detail. This task will involve cross-referencing between multiple datasets and online research to identify schools that have changed names or ID numbers over time. The Research Assistant will then be tasked with a data collection project. The Research Assistant will conduct online research to identify relevant school district policies from 22 large U.S. school districts and compile this information into a database.

 

Desired qualifications: We are looking for an undergraduate or Master’s level student from any discipline. Interested students must be detail-oriented and experienced in using Excel and conducting internet-based research. Students must also be willing to learn the basics of QGIS software, but I will provide all the necessary training, so prior experience is not necessary.

Contact: Elly Field, PhD Candidate in Sociology, emfield@umich.edu

Date Posted
4/21/2021

The Laboratory of Integrated Brain Imaging (PI: Dr. Zhongming Liu)

The Laboratory of Integrated Brain Imaging (PI: Dr. Zhongming Liu) has multiple positions available for undergraduate and graduate students to work for research during Summer 2021. As a temporary worker (or a summer intern), each student will be paid for on an hourly basis. Preference will be given to the students who are likely to extend the work to Fall 2021 or research for master thesis.

Job 1: Animal MRI image analysis

The student will work with the PI and existing graduate students to develop and test an MRI image processing pipeline for automated analysis of gastrointestinal MRI. The pipeline to be established will include image denoising, co-registration, motion correction, segmentation, 3D surface modeling, rendering. A strong candidate should have strong programming skills (Python and Matlab), knowledge with image and signal processing and optimization, good work ethics and commitment to teamwork. An ideal candidate should have experiences with machine learning, especially deep learning (using PyTorch).

Job 2: Animal fMRI analysis pipeline

The student will work with the PI and existing graduate students to develop and test a processing pipeline for online and offline analysis of animal fMRI images. The pipeline to be established will include image denoising, filtering, motion correction, co-registration, segmentation, surface modeling and rendering, as well as statistical parametric mapping with linear regression, statistical tests, principal or independent component analysis, functional connectivity etc. A strong candidate should have strong programming skills (Python and Matlab), knowledge with image and signal processing, optimization methods, good work ethics and commitment to teamwork. An ideal candidate should have knowledge with either animal or human brain mapping, system neuroscience.

Job 3: Representation learning of fMRI activity

The student will work with the PI and existing graduate students to develop, test and document deep learning methods for representation learning of human brain activity. The methods to be developed will include deep learning with neural networks, e.g., variational autoencoder, recurrent neural networks, Transformer, graph neural networks. Part of this job will involve documentation, testing, and application of existing methods already developed in the lab. A strong candidate should have strong programming skills, prior experiences with deep learning (PyTorch or TensorFlow) in the context of medical image analysis, computer vision or natural language processing, good work ethics and commitment to teamwork.

Job 4: Animal MRI and electrophysiology

The student will need to work in the lab and assist in vivo animal experiments that involve animal (rodents) MRI, neuromodulation, and electrophysiology. A strong candidate should have interest and background in biomedical engineering and neuroscience. An ideal candidate should have prior experiences with animal handling, surgery, behavioral testing, electrophysiology. Experiences with data analysis and programming are desirable but not required.

For any inquiry, please contact Dr. Zhongming Liu (zmliu@umich.edu). 

Date Posted
4/15/2021

Cancer Metabolism and Precision Medicine (Sriram Chandrasekaran, Biomedical Engineering)

Project Summary
This project involves the application of computer models to simulate the metabolic properties of tumors. The computer models will be built using genomics, metabolomics and transcriptomics data from various types of cancer cell lines. By understanding the unique metabolic properties of each cell type, we can design drugs that target specific tumors. Further, knowledge of these differences will be used to design synergistic drug combinations tailored to each patient.

Responsibilities
The project involves data collection, model construction, simulation, analysis, testing,  and literature review. Estimated 8 hours per week of work.

Required Experience
Preferred skills: Familiarity with MATLAB or Python. Basic knowledge of biochemistry, molecular biology and genetics. Experience working with big-data (genomics, transcriptomics) and knowledge of machine-learning.

Compensation
Students may register for independent research credit.

Contact
csriram@umich.edu

Date Posted
1/19/2021

Representation Learning of Brain Activity (Zhongming Liu, Biomedical Engineering, Electrical & Computer Engineering)

Project Summary
Representation learning of brain activity. Learning algorithms are designed to represent and decode brain activity, e.g. to reconstruct human vision, speech, language, or dream. Abundant data are available from human or animal brains.

Responsibilities
The project involves data analysis, writing code, and literature analysis. Estimated 5-10 hours per week of work.

Required Experience
Graduate or senior undergraduate students in computer science, electrical engineering, biomedical engineering, statistics, or mathematics. Ideal candidates should have completed courses related to machine learning, especially deep learning, and experiences with PyTorch or TensorFlow.

Compensation
Hourly pay is available, Students may register for independent research credit

Contact
zmliu@umich.edu

Date Posted
1/19/2021

Summer GSRA Positions: Kindergarten Societies, Children’s Decisions, and Heath

Description: Elizabeth Bruch (Sociology & Complex Systems) is seeking to hire two students to help launch a new project on the social structure of kindergarten classrooms and the implications of this structure for children’s decisions about who to interact with and their health and well-being. This project draws on a unique and rich dataset documenting interactions among children in kindergarten classrooms, as well as family demographics for the children and a host of measures reporting their physical and mental health over multiple periods of time. There are two aims: (1) to calculate the social rank of children in different classrooms according to a variety of network measures, and to examine correlates of social rank (e.g., sex, mental health, family SES); (2) to determine whether some classrooms are more hierarchical than others, and how overall levels of inequality in the classroom interact with children’s rank to shape health outcomes. This project is perfect for students interested in social hierarchies and social structure, experiences in childhood, and/or health disparities.

Position 1 is for someone with excellent writing and organizational skills who has the tenacity to comb through a sprawling set of files associated with the data and produce a coherent and hyperlinked set of documentation. This person will also produce a set of data files along with documentation about what each file contains, so some basic statistical skills will be needed. This position could be filled by an exceptional undergraduate, or a Masters or PhD student.

Position 2 is for someone with strong quantitative training and excellent communication skills, who will conduct statistical analysis for our research project. The desired qualifications for this position include experience with multilevel models and network analysis, research experience, comfort working in Python as well as either Stata or R, and energy and enthusiasm for interdisciplinary collaboration. If the person makes a sustained contribution to the project over the summer, there is a possibility of co-authorship and potentially a GSRA position for the fall.

Dates: The work runs from May through August. Position 1 is 10-15 hours per week, Position 2 is 20 hours per week. Work can potentially be done remotely.

Salary and benefits: Position 1: $18-20 per hour; Position 2: $20-25 per hour.

How to apply: Please email your cover letter describing your interest and fit for the position,

CV, and a copy of your unofficial transcript to Elizabeth Bruch (ebruch@umich.edu).

Deadline to apply: Applications will be reviewed as they come in.

Date Posted: 3/24/2021

Work as a Part of a Team to Develop a Knowledge Network (Tayo Fabusuyi, College of Engineering)

Project Summary: 

As part of a public interest technology (PIT) grant from New America, we require the services of students that will provide input on both the front and the backend development of a Knowledge Network. Our team will be building this platform to facilitate connection, interaction and collaboration among persons of color who are active in the area of public interest technology.

Experience Required:

  • Backend: Students with good working knowledge of Python, Java, PHP, Ruby or other similar backend programming languages
  • Frontend: Students with good working knowledge of Javascript, HTML, CSS or other similar frontend programming languages
  • A mindset of collaboration and community building
  • Good teamwork and organizational skills, attention to details, and strong work ethic
  • Great interpersonal and communication skills (oral and written)
  • Being able to work independently when given clear instructions

Time Frame:

  • Flexible. We anticipate around 8-10 hours per week. The project duration may be anywhere between 12 to 18 weeks.
  • This project will run from Summer till the end of Fall 2021

Compensation:

  • Hourly Pay is Available, Students may register for independent research credit

For more information, please contact fabusuyi@umich.edu 

Date Posted: 3/24/2021

Research Assistant for Data Equity, Justice, and Policy Project

Research Assistant for Data Equity, Justice, and Policy Project Position Announcement

The Science, Technology, and Public Policy Program in the Ford School of Public Policy is searching for a research assistant to work with a postdoctoral fellow and faculty (in both the Ford School and the Michigan Institute for Data Science) on a project focused on reimagining University of Michigan’s undergraduate computer science curriculum with equity and justice at its core. This is a unique opportunity for an undergraduate or graduate student interested in bringing public interest and social justice concerns into science and technology practice and education.

The summer intern will learn how to produce case studies on equity and justice in data science and technology, conduct literature reviews, conduct interdisciplinary research at the intersection of technology, social science, and public policy, and work in an interdisciplinary team. They will also learn how to communicate, both orally and in written form, across disciplinary audiences.

The ideal candidate will:

  • Be a University of Michigan undergraduate or graduate student
  • Be available to work part time during the spring and summer terms. There may also be the possibility of continued part time work into the 2021-2022 academic year.
  • Have an interest in data, technology, equity, and public policy
  • Be self-motivated and task oriented, able to execute tasks independently to move project forward
  • Have strong organizational skills and attention to detail
  • Be able to work independently to solve problems
  • Have excellent writing skills, and be able to synthesize complex findings from multiple sources clearly and concisely in written form
  • Be able to communicate openly and transparently

 

Hours averaging 10-20 hours/week at $12-$18/hour, depending on experience. Position begins the week of May 3rd, 2021 Work location: Remote.

If interested, please apply at http://studentemployment.umich.edu, job reference # 65124, with a letter of interest detailing your relevant experience, a short writing sample (e.g. policy memo, blog post, op-ed, essay) and resume no later than Monday April 12th.

Previous Student Research Assistant Positions

System for Opioid Overdose Surveillance (SOS) Data Dashboard (Web Site Designer, UM Injury Prevention Center)

The University of Michigan Injury Prevention Center is seeking a highly motivated individual to maintain the System for Opioid Overdose Surveillance (SOS) data dashboard which collects suspected fatal and non-fatal opioid overdoses and is updated on a daily basis. The SOS dashboard is fully constructed and is currently used by over 300 public health and public safety stakeholders in the state of Michigan. The primary function of this position is to perform day-to-day maintenance of the dashboard to ensure new data is uploaded and integrated in a timely manner, and that all dashboard functions continue to perform as intended. The position requires web- development skills, database management, and GIS skills. Candidate should have strong understanding of data science and geo-spatial concepts and be familiar with using Python.  Examples of tasks performed include:

  • Upload new data onto the SOS server and database, and run error checking codes to identify deviations from expected format
  • Geocode incident locations and perform consistency checks to minimize geocoding error rates
  • Take incident reports from SOS staff and stakeholders on issues encountered with the interface and identify and correct the causes
  • Test dashboard functions to ensure they continue to perform as intended and, if applicable, identify and correct the cause of any bugs
  • Change aesthetic and basic functionality of the dashboard in response to stakeholder feedback if applicable
  • Perform data turnover routines as specified in our data use agreements (e.g., eliminating identifiers after six months)

For additional details or to apply for the position, visit: https://studentemployment.umich.edu/jobxJobdetailPrint.aspx?JobId=65201&win=True. Please email Amanda Ballesteros at amandkog@med.umich.edu with any questions.

Capacity Building Teaching Assistant Position (Internship Opportunity)

What is IRIS? 

IRIS is a consortium of research universities anchored on an IRB-approved data repository with the goal of understanding, explaining and improving research and higher education. It is housed  at the Institute for Social Research (ISR) at the University of Michigan. ISR is the world’s largest academic social science survey and research organization and conducts some of the most widely-cited and influential social science research in the world.

What does IRIS do? 

IRIS ingests member university administrative data related to research awards into a highly protected data enclave environment and makes linkages to Census Bureau data and other datasets. Using these integrated datasets, IRIS generates reports demonstrating the career trajectory of research staff, vendor spending, as well as other measures of impact. IRIS makes these combined datasets available for research in a virtual data enclave. Iris.isr.umich.edu

IRIS Teaching Assistant

This is a student support position for an online educational workshop that IRIS will conduct in early June 2021.  This workshop teaches participants who have limited quantitative analytical skills how to work with large datasets to perform data analysis using Python. The goal is to train cohorts of researchers in education and the social sciences to be able to answer research questions using big data This position will serve as a teaching assistant and technical support for the workshop as well as help prepare and test the data and code prior to the start of the course. During the course, teaching assistants will be assigned a team of learners (faculty, postdocs, and graduate students) and will provide support to this group via office hours and for a month or so following its conclusion (by about mid-July).  This opportunity could be used for internship credit and exceptional performance may result in additional work during the remainder of the summer.

 

Hours

May 3-May 14: 20 hours per week

May 17-June 11: 40 hours per week

June 14-July 30: 20 hours per week

August 2-September 3: TBD

 

At the moment, the IRIS team is working from home until we are directed to return to the office in the Perry Building.

 

How to apply

To apply for this position please send a resume and cover letter to Nancy Calvin-Naylor (nbirk@umich.edu), IRIS Managing Director.

 

Primary responsibilities:

  • Contribute to efforts to develop instructional materials by adapting existing material, data, and exercises for training opportunities.

      Provide technical and research support to learners by responding to data and technical questions in training settings, as well as providing ongoing participant support as needed.

Required qualifications:

      Proficiency in Python (Jupyter Notebooks)

      Understanding of SQL

      Excellent oral and written communication skills

      Strong attention to detail

      Ability to work well within a team as well as independently

Desired qualifications:

Master’s degree  (Or in progress Master’s degree) in relevant field

Experience with supporting/communicating with non-technical audience

Support Native American tribes in their effort to build an education data system (MIDAS Research Assistant Position)

Job description: The Michigan Institute for Data Science (MIDAS) organizes a large number of research, training and outreach activities, including supporting governments and non-profit organizations for their data needs. MIDAS is seeking 1-3 students to participate in a project that supports the Native American tribes in their effort to build an education data system.

The students will work with faculty mentor Dr. Tayo Fabusuyi and the education leaders of the tribes to make recommendations and design databases and dashboards with human-centered and socially responsible design principles. The students will also help the tribes onboard the new databases and dashboards. 

Qualifications: 

  • Graduate or undergraduate students with a background in database development and UI;
  • Having taken data science classes is a plus;
  • A mindset of community service and respect for the Native American culture;
  • Good organizational skills, attention to details, and strong work ethic;
  • Great communication skills (oral and written);
  • Being able to work independently when given clear instructions, as well as skills for teamwork.

Educational value of the project: This is an unpaid volunteer experience. Students will not only gain research experience, but will also learn the Native American culture and gain skills on how to support the community through data projects.   

Time commitment: Around 10 hours per week (flexible schedule), starting ASAP. The project duration will depend on the needs of the Native American tribes, and may be anywhere between 4 to 12 weeks.

To apply, please upload your resume