Principal Scientist — AI-Powered Discovery for Neurodegeneration

Sanofi•Cambridge, MA

1d•$122,250 - $176,583•Onsite

About The Position

As a Principal Scientist within the Neurology Research Team you will lead machine learning/AI based discovery efforts to advance research programs focused on Alzheimer’s, Parkinson’s, ALS/FTD, and Multiple Sclerosis. You will join a team to lead the analyses of large scale public and internal data sets from human brain tissue single cell and spatial omics (rna, protein and lipids), fluid proteogenomic biomarkers (CSF and plasma), and functional screening (CRISPR) in human disease relevant cell models. You will help uncover causal molecular and cellular mechanisms of disease by employing state-of the art Machine Learning/AI methods on the above data sets to accelerate new target and biomarker discovery efforts. Join the engine of Sanofi’s mission - where deep neuroscience meets bold, AI-powered research. In R&D, you’ll drive breakthroughs that could turn the impossible into possible for millions

Requirements

Bachelor's degree in Biology, Biochemistry, Bioengineering, Computer Science, Mathematics, Statistics, Physics, Neuroscience, or related quantitative/life science fields, followed by a Ph.D. in Computational Biology, Bioinformatics, Neuroscience, or related fields.
Minimum 4+ years of post-PhD experience in the biotech industry or academic institution, with a strong track record in computational biology applied to neurodegenerative diseases.
Deep expertise in analyzing large-scale datasets including multi-omics, single-cell genomics, and spatial transcriptomics.
Proven experience in neurodegenerative disease research, specifically Alzheimer's disease (AD), Parkinson's disease (PD), Multiple Sclerosis (MS), and ALS/FTD.
Human Brain Genomics Expert: Demonstrated experience analyzing human brain single-cell genomics datasets and/or CSF/PBMC atlases.
Proteomic Analysis: Proven ability to analyze proteomic datasets from neurodegenerative disease patient tissue or biofluids.
Model Systems Knowledge: Deep understanding of omics analyses in mouse and cellular models of neurodegenerative disease.
Advanced Analytical Workflows: Expertise in developing analytical workflows for discovering and quantifying cryptic splices in scRNAseq, long-read, and spatial transcriptomics datasets.
AI/ML Proficiency: Proven experience using AI/ML models to explore cell gene regulatory landscapes of disease-associated cell states from single-cell transcriptomic, ATACseq, and cryptic splicing datasets.
Foundational Knowledge: Broad technical skills and deep foundational knowledge of neuroscience, bioinformatics, pharmacology, life science, and statistics.
Publication Record: Track record of impactful scientific achievement as demonstrated by co-first/lead as well as contributing author publications.
Excellent communication skills and evidence of success in complex, multidisciplinary environments are required.

Nice To Haves

Highly motivated and driven with strong collaborative skills.
Excels working in collaborative teams with diverse expertise.
Ability to relate computational analyses with clarity and precision to non-computational stakeholders.
Strong problem-solving skills and ability to work independently in a fast-paced research environment.

Responsibilities

Leading and implementing the full-scale analyses, integration and harmonization of omics data sets to deliver a decision-grade resource for neurology TA.
Integrate single-cell genomics with plasma and CSF proteomics and clinical outcomes from public and in-house datasets to identify cell state shifts and molecular features associated with disease progression, contributing to refining patient selection criteria for future trial designs.
Champion the 'Everyday AI' initiative to establish a baseline of AI literacy across the Neurology TA.
Lead cross-functional upskilling programs to ensure universal digital fluency, accelerating productivity by integrating AI tools into daily non-technical and technical workflows.
Lead authorship of impactful scientific publications.