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Biological Data Science Internship Jobs in Michigan

Provide feedback and domain-specific insights to improve AI models in computational biology contexts. * Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with ...

Provide feedback and domain-specific insights to improve AI models in computational biology contexts. * Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with ...

Provide feedback and domain-specific insights to improve AI models in computational biology contexts. * Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with ...

Provide feedback and domain-specific insights to improve AI models in computational biology contexts. * Evaluate scientific content for accuracy, relevance, and clarity, ensuring data aligns with ...

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Biological Data Science Internship information

What are the key skills and qualifications needed to thrive as a biological data science intern, and why are they important?

To thrive as a Biological Data Science Intern, you need a solid background in biology, statistics, and programming, often supported by coursework or a degree in bioinformatics or a related field. Familiarity with tools like Python, R, and data analysis platforms, as well as experience with genomic databases and visualization software, is typically expected. Strong problem-solving, attention to detail, and teamwork skills help interns excel in collaborative research environments. These abilities enable accurate analysis of complex biological data and contribute to meaningful scientific discoveries.

What types of projects do interns typically work on during a biological data science internship?

Biological Data Science interns often work on projects involving the analysis of large biological datasets, such as genomic, proteomic, or clinical data. Typical tasks may include cleaning and preprocessing data, developing statistical models, and visualizing complex biological patterns. Interns frequently collaborate with both data scientists and biologists, gaining exposure to interdisciplinary teamwork and real-world research challenges. This hands-on experience helps interns build both their technical and scientific communication skills, making it a valuable stepping stone for careers in bioinformatics, computational biology, or related fields.

What is the difference between Biological Data Science Internship vs Biological Data Analyst?

AspectBiological Data Science InternshipBiological Data Analyst
Required CredentialsUndergraduate or graduate student in biology, data science, or related fieldBachelor's or master's in biology, data science, or related field; sometimes requires experience
Work EnvironmentResearch labs, biotech companies, academic institutions, often temporary or project-basedCorporate or research settings, ongoing role with regular hours
Employer & Industry UsageInternships offered by biotech firms, research institutions, universitiesFull-time roles in biotech, pharmaceuticals, research organizations

The Biological Data Science Internship is typically a temporary, entry-level position aimed at students gaining practical experience, whereas a Biological Data Analyst is a full-time role requiring more experience and responsibility. Internships focus on learning and skill development, while analysts handle ongoing data analysis tasks in professional settings.

What is a biological data science internship?

A Biological Data Science Internship is a temporary position for students or recent graduates to gain practical experience working at the intersection of biology and data science. Interns typically analyze biological datasets using computational tools, statistical methods, and programming languages such as Python or R. They may work on projects involving genomics, bioinformatics, drug discovery, or ecological modeling. The internship helps individuals develop both technical and domain-specific skills, preparing them for future careers in research, biotechnology, or academia.
What job categories do people searching Biological Data Science Internship jobs in Michigan look for? The top searched job categories for Biological Data Science Internship jobs in Michigan are:
What cities in Michigan are hiring for Biological Data Science Internship jobs? Cities in Michigan with the most Biological Data Science Internship job openings:

Senior Data Scientist - Multiomics and Population Cohorts

University of Michigan

Ann Arbor, MI • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 8 days ago


University Of Michigan rating

8.1

Company rating: 8.1 out of 10

Based on 144 frontline employees who took The Breakroom Quiz

156th of 616 rated colleges and universities


Job description

Mission Statement
Michigan Medicine improves the health of patients, populations and communities through excellence in education, patient care, community service, research and technology development, and through leadership activities in Michigan, nationally and internationally. Our mission is guided by our Strategic Principles and has three critical components; patient care, education and research that together enhance our contribution to society.
Job Summary
The Division of Cardiovascular Medicine at the University of Michigan is expanding a nationally and internationally funded research program at the cutting edge of cardiovascular medicine. Led by Drs. Venkatesh Murthy and Sascha Goonewardena - whose work has appeared in leading journals including NEJM AI, JAMA, and Circulation - the program fuses artificial intelligence, advanced cardiac imaging, multiomics (proteomics, metabolomics, and genomics), and cardiometabolic disease biology to develop precision diagnostics and identify novel therapeutic approaches, with a particular focus on coronary microvascular disease and other cardiovascular conditions that disproportionately affect women and remain poorly served by existing diagnostic tools. This is a rare opportunity to join a high-impact, well-funded program doing science that matters.
This position serves as the primary multiomics computational scientist for the program. The incumbent will build and maintain proteomics and multi-omic analysis pipelines, deploy AI model inferences at scale in large population biobanks, and apply causal and genetic inference methods to identify biological mechanisms underlying cardiometabolic disease. This is an infrastructure and pipeline-focused role: the incumbent constructs the computational frameworks and cross-cohort data systems that make population-scale discovery possible, working closely with the postdoctoral scientist who leads the hypothesis-driven analyses and manuscript development. This is one of two senior data scientist roles; the two positions serve complementary, non-overlapping functions.
Responsibilities*
  • Build, implement, and maintain proteomics and multi-omic analysis pipelines integrating high-throughput proteomic data with metabolomic, genomic, and clinical datasets from large prospective cohort studies
  • Deploy AI models to biobank datasets
  • Build and maintain cross-cohort data harmonization and proteomic cross-walk tools across derivation and validation datasets
  • Perform causal and genetic inference analyses (including Mendelian randomization and mediation analysis) to identify disease mechanisms
  • Evaluate pipeline and signature performance; prepare written and code-based analytical reports (Python or R)
  • Contribute to manuscripts, grant applications, and presentations
  • Coordinate data sharing and computational workflows with collaborative network partners and other research partners
  • Other duties as assigned

Required Qualifications*
  • Masters or doctoral degree in bioinformatics, computational biology, biostatistics, systems biology, or a closely related field
  • Demonstrated experience analyzing large-scale proteomic datasets from high-throughput platforms (Olink or SomaScan)
  • Proficiency in R and/or Python for statistical analysis and pipeline development
  • Experience with multi-omic data integration combining at least two of: proteomics, metabolomics, genomics, transcriptomics
  • Familiarity with statistical methods for high-dimensional biological data (dimensionality reduction, regularized regression, survival analysis
  • Strong organizational skills and attention to detail
  • Ability to prepare and present written and code-based (Python or R) analytical reports
  • Strong scientific writing skills; ability to contribute to manuscripts and grant applications

Desired Qualifications*
  • Experience with large prospective cohort or biobank datasets (e.g., CARDIA, MESA, Framingham Heart Study, UK Biobank, or similar)
  • Experience with mediation analysis, causal inference, or Mendelian randomization methods in an omics context
  • Background in cardiovascular biology, vascular biology, or cardiometabolic disease
  • Experience with cloud or HPC computing environments, including Slurm-based job scheduling
  • Familiarity with SQL or PostgreSQL for data querying and management
  • Track record of peer-reviewed publications as a computational contributor to biomedical research
  • Familiarity with endothelial biology, inflammation, or microvascular disease
  • Experience with Git and reproducible research practices ? Experience building reproducible pipelines using workflow managers (Snakemake, Nextflow, or equivalent)

Why Join Michigan Medicine?
Michigan Medicine is one of the largest health care complexes in the world and has been the site of many groundbreaking medical and technological advancements since the opening of the U-M Medical School in 1850. Michigan Medicine is comprised of over 30,000 employees and our vision is to attract, inspire, and develop outstanding people in medicine, sciences, and healthcare to become one of the world's most distinguished academic health systems. In some way, great or small, every person here helps to advance this world-class institution. Work at Michigan Medicine and become a victor for the greater good.
What Benefits can you Look Forward to?
  • Excellent medical, dental and vision coverage effective on your very first day
  • 2:1 Match on retirement savings

Modes of Work
Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes .
Work Schedule
Work Schedule: Monday through Friday, standard business hours. This is an onsite position.
Additional Information
We, the staff and faculty of the U-M Cardiovascular Center (CVC) team, are committed to advancing medicine and serving humanity through living and teaching our core values of Respect and Compassion; Collaboration; Innovation; and Commitment to Excellence. Each CVC employee is expected to understand and demonstrate that in every interaction we represent our entire organization in the care we provide and in the courtesies we extend to patients, families, and each respective team member. The CVC is dedicated to partnering with patients and families to deliver the safest and highest quality of health care.
The Division of Cardiovascular Medicine is firmly committed to advancing inclusion, diversity, equity, accessibility, and belonging, which are core to the culture and values of the Medical School Office of Research. Our community supports recruiting and cultivating a diverse workforce as a reflection of our commitment to serve the diverse people of Michigan and the world. We strive to create a work culture where each team member feels respected, valued, and safe.
Background Screening
Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings. Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.
Application Deadline
Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.
U-M EEO Statement
The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.
Job Detail
Job Opening ID
280230
Working Title
Senior Data Scientist - Multiomics and Population Cohorts
Job Title
Bioinfo-Comput Biologist Sr
Work Location
Ann Arbor Campus
Ann Arbor, MI
Modes of Work
Onsite
Full/Part Time
Full-Time
Regular/Temporary
Regular
FLSA Status
Exempt
Organizational Group
Medical School
Department
MM Int Med-Cardiology
Posting Begin/End Date
7/30/2026 - 8/27/2026
Career Interest
Research

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About University of Michigan

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The University of Michigan (U-M), based in Ann Arbor, MI, US, is one of America's most esteemed institutions in higher education. Established in 1817, it presides in the industry of education and research, providing a range of services including undergraduate, graduate, and professional education programs. Complementing this is an extensive research activity that has significantly contributed to various fields, from healthcare to engineering, humanities to sports. Upholding its mission "to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values", U-M consistently ranks among the top universities globally, a testament to its tradition of excellence in learning and research, and a deep commitment to innovation and discovery.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Ann Arbor, MI, US

Year founded

1817

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