Postdoctoral Research Fellow Lab Medicine and Pathology

We are seeking a highly motivated Research Fellow to join a pathologist-led research program focused on machine learning applications and disease-mechanism discovery in steatohepatitis. The fellow will contribute to building a multimodal research dataset integrating EHR-derived clinical variables laboratory data whole-slide pathology images (WSI) and spatial biology outputs enabling translational and AI/ML studies.

This is a mentored scholarly training role intended to develop the professional skills needed for an academic/research career.

By the end of the appointment period the fellow is expected to be able to:

Design and document reproducible cohort selection logic using EHR and lab data (inclusion/exclusion phenotyping rules data definitions)

Perform and/or oversee high-quality chart review and structured data abstraction with rigorous QC and documentation

Support WSI workflows (case/slide organization metadata linkage review logging) and coordinate linkage to spatial biology results

Contribute to a research-ready multimodal dataset (data dictionary elements variable provenance harmonization notes QC checklists)

Produce scholarly outputs including abstracts/manuscripts and where appropriate pilot analyses that support downstream ML modeling and mechanistic hypotheses

Expected outcomes include a documented dataset module or milestone (e.g. a validated cohort curated feature set linked image/spatial metadata) and progress toward peer-reviewed publication during the appointment with mentorship support.

Key responsibilities (research scholarly development)

Mastery of python codingincluding but not limited machine learning training using pytorch and mastery of bioinformatics analysis tools.

Cohort identification/selection; protocol-driven eligibility screening

Chart review and clinical variable abstraction; creation of clean research tables and tracking logs

Whole-slide image organization and review support (as project-appropriate)

Literature management (EndNote) and contribution to study documentation

Participation in lab meetings and project updates; completion of an Individual Development Plan (IDP)

Manuscript/abstract preparation and submission support; encouraged to pursue extramural funding opportunities

Must have a Ph.D. M.D. or equivalent doctoral degree in a field deemed relevant by the program.

Preferred qualifications

Experience with digital pathology / WSI image metadata organization or computational pathology workflows

Experience with or strong interest in clinical data (EHR/labs) translational research or pathology-related research

Proficiency with Excel Word and EndNote.

Mastery of Python coding (data cleaning analysis pipelines automation)

Prior publications and experience in team-based research