Assoc. Scientist, Post Doc Fellow- Data Science for Multi-omics and Biomarker Modeling in Neuroscience
Core
Develop and apply novel AI/ML methods linking biofluid biomarkers with tissue-based multi-omics to drive precision patient subtyping and predictive modeling in neurodegenerative diseases, primarily Alzheimer's disease.
Role type
Postdoctoral Research Fellow, Data Science for Multi-omics and Biomarker Modeling
Builds
End-to-end ML/DL pipelines, novel algorithms, benchmarked models, and reusable codebases for in silico target perturbation and biomarker dynamics prediction.
Domain
Neuroscience, Biopharmaceuticals, Multi-omics, AI/ML
Deliverable
production ML models
Required skills
Python, Deep Learning frameworks (PyTorch), Multi-omics integration, Statistical analysis, Mathematical modeling, Scientific writing, Data harmonization, Algorithm development
Preferred skills
Alzheimer's disease biology, Biomarker discovery, Patient stratification, Graph/network methods, Causal inference
Technologies
PyTorch, Python
Responsibilities
Design and implement end-to-end AI/ML pipelines for biomarker discovery; Develop and innovate on ML/DL methods tailored to study objectives; Build and benchmark models for patient subtyping and progression prediction; Translate model outputs into actionable insights via visualizations and APIs; Develop high-quality documentation and internal tools; Collaborate with partners on study design and data interpretation; Contribute to scientific communication through publications and presentations.
Seniority
Postdoctoral Fellow, Research & Development
