1

Causal Inference Machine Learning Postdoctoral Jobs in Michigan

Be Seen First

ANOVA, principal component analysis, correspondence analysis, k-means clustering, factor analysis, multi-variate analysis, Neural Networks, causal inference, Gaussian regression, etc. 3+ Experience ...

New

Senior Data Analyst

Detroit, MI · On-site +1

$96K - $132K/yr

Lead the design, development, and implementation of advanced machine learning models and algorithms ... Strong understanding of A/B testing, experimental design, and causal inference techniques.

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director ... Proven ability to develop production-grade ML applications for training, evaluation and inference ...

next page

Showing results 1-20

Causal Inference Machine Learning Postdoctoral information

What is a Causal Inference Machine Learning Postdoctoral researcher?

A Causal Inference Machine Learning Postdoctoral researcher is a scientist who specializes in developing and applying machine learning methods to understand cause-and-effect relationships in data. They typically hold a recent PhD in statistics, computer science, economics, or a related field, and work in academic or industry research settings. Their work involves designing experiments, analyzing complex datasets, and creating models that can infer causal relationships, which are crucial for making robust predictions and informed decisions. This role often collaborates with interdisciplinary teams to apply these techniques to domains such as healthcare, social science, or economics.

What are the key skills and qualifications needed to thrive as a Causal Inference Machine Learning Postdoctoral researcher, and why are they important?

To thrive as a Causal Inference Machine Learning Postdoctoral researcher, you need a strong background in statistics, causal inference methodologies, and advanced machine learning, usually evidenced by a PhD in a relevant field. Familiarity with programming languages such as Python or R, experience using statistical software (e.g., TensorFlow, PyTorch, Stan), and knowledge of causal inference libraries are typically required. Outstanding analytical thinking, problem-solving abilities, and strong communication skills help you collaborate effectively and explain complex concepts to diverse audiences. These skills and qualifications are vital for advancing research, deriving actionable insights from data, and contributing to impactful scientific discoveries.

What are some common challenges faced by Causal Inference Machine Learning Postdoctoral researchers when integrating causal models with real-world data?

Causal Inference Machine Learning Postdoctoral researchers often encounter challenges such as dealing with unobserved confounding variables, ensuring data quality, and addressing biases inherent in observational datasets. Integrating advanced machine learning techniques with causal inference frameworks requires careful consideration of model assumptions and validation methods. Collaboration with domain experts is essential to properly interpret results and to translate findings into actionable insights, especially in interdisciplinary settings like healthcare or social sciences.

What is the difference between Causal Inference Machine Learning Postdoctoral vs Data Scientist?

AspectCausal Inference Machine Learning PostdoctoralData Scientist
Required CredentialsPhD in statistics, machine learning, or related fieldBachelor's or Master's in data science, computer science, or related field
Work EnvironmentAcademic research, research labs, universitiesCorporate, tech companies, startups
Industry UsageResearch, academia, specialized industry projectsBusiness analytics, product development, data-driven decision making
Common Search/ComparisonYesYes

The main difference is that Causal Inference Machine Learning Postdoctoral roles focus on academic research and developing new methods in causal inference, often requiring a PhD. Data Scientists typically work in industry, applying existing models to solve business problems, with a focus on data analysis and visualization. While both roles involve machine learning, the postdoctoral position emphasizes research and theory, whereas data science emphasizes practical application.

What are popular job titles related to Causal Inference Machine Learning Postdoctoral jobs in Michigan? For Causal Inference Machine Learning Postdoctoral jobs in Michigan, the most frequently searched job titles are:

Postdoctoral Research Fellow - Multiomics and Causal Inference

University of Michigan

Ann Arbor, MI • On-site

$47K - $65K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 6 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

152nd of 612 rated colleges and universities


Job description

Who We Are
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.
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 postdoctoral position offers an exceptional opportunity for a highly motivated researcher to lead the hypothesis-driven discovery work of the program's omics and causal inference work streams, under the primary supervision of Dr. Murthy, with close collaboration with Dr. Goonewardena and a broad network of national and international research partners. The fellow will lead multi-omic analyses using pipelines built by the program's computational team, drive causal inference studies in biobank-scale datasets, and translate findings into first-author publications. This role emphasizes scientific leadership, discovery, and manuscript development. Appointments are made on an annual basis and are renewable, with a maximum total duration of three years, contingent on satisfactory performance and continued funding.
Responsibilities*
  • Develop and apply analytical pipelines integrating high-throughput proteomic data with metabolomic, genomic, and clinical datasets from large prospective cohort studies to identify biological signatures of coronary microvascular disease and cardiometabolic disease
  • Perform causal and genetic inference analyses - including Mendelian randomization and mediation analysis - in biobank-scale datasets
  • Prepare first-author manuscripts for peer-reviewed journals and present work at national and international scientific meetings
  • Contribute to grant applications, progress reports, and preliminary data generation for future funding
  • Participate in laboratory meetings, journal clubs, and collaborative program activities
  • Contribute to mentoring of junior trainees
  • Other duties as assigned

Required Qualifications*
  • Doctoral degree (PhD, MD/PhD, or MD) in computational biology, bioinformatics, biostatistics, cardiovascular biology, epidemiology, or a closely related field
  • Experience with proteomic, metabolomic, or other omic data analysis in a research context
  • Proficiency in R and/or Python for statistical analysis and pipeline development
  • Familiarity with causal inference or genetic epidemiology methods (e.g., Mendelian randomization, mediation analysis)
  • Strong scientific writing and oral communication skills
  • Demonstrated ability to drive projects to completion independently

Desired Qualifications*
  • Experience with large prospective cohort or biobank datasets (CARDIA, MESA, Framingham Heart Study, UK Biobank, or similar)
  • Experience with high-throughput proteomic platforms (Olink or SomaScan)
  • Background in cardiovascular biology, vascular biology, or cardiometabolic disease
  • Track record of peer-reviewed publications relative to career stage
  • Experience with multi-omic data integration
  • Familiarity with HPC or cloud computing environments

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
Monday through Firday, standard business hours.
Work Locations
This is an onsite position.
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 any time 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
280575
Working Title
Postdoctoral Research Fellow - Multiomics and Causal Inference
Job Title
RESEARCH FELLOW
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
7/24/2026 - 8/21/2026
Career Interest
Research Fellows

What University Of Michigan employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


University of Michigan logo

About University of Michigan

Sourced by ZipRecruiter

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

Social media