Sanofi
biopharma
PrincipalScientist—AIPoweredDiscoveryforNeurodegeneration
“Principal Scientist — AI-Powered Discovery for Neurodegeneration at Sanofi. Skills: AI/ML, computational biology, neuroscience, multi-omics analysis, single-cell genomics, spatial transcriptomics. Lead machine learning/AI based discovery efforts to advance research programs focused on Alzheimer’s, Parkinson’s, ALS/FTD, and Multiple Sclerosis. 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 prote”
What You'll Achieve.
deliver a decision-grade resource for neurology TA; identify cell state shifts and molecular features associated with disease progression; refining patient selection criteria for future trial designs; accelerating productivity by integrating AI tools into daily non-technical and technical workflows; Lead authorship of impactful scientific publications; accelerate new target and biomarker discovery efforts
Industry & Context.
problem-solving skills
What They're Looking For.
Must Have
Bachelor's degree in Biology, Biochemistry, Bioengineering, Computer Science, Mathematics, Statistics, Physics, Neuroscience, or related quantitative/life science fields, Minimum 4+ years of post-PhD experience in the biotech industry or academic institution, with a 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, 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 Have
Ph. D. in Computational Biology, Bioinformatics, Neuroscience, or related fields, Highly motivated and driven with collaborative skills, Excels working in collaborative teams with diverse expertise, Ability to relate computational analyses with clarity and precision to non-computational stakeholders, problem-solving skills and ability to work independently in a fast-paced research environment
What You'll Do.
Lead machine learning/AI based discovery efforts to advance research programs focused on Alzheimer’s
and Multiple Sclerosis
Lead the analyses of large scale public and internal data sets from human brain tissue single cell and spatial omics (rna
fluid proteogenomic biomarkers (CSF and plasma)
and functional screening (CRISPR) in human disease relevant cell models
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
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
How You'll Work.
Team & Collaboration
Lead cross-functional upskilling programs; Excels working in collaborative teams with diverse expertise; Ability to relate computational analyses with clarity and precision to non-computational stakeholders
Communication Scope
Excellent communication skills; Ability to relate computational analyses with clarity and precision to non-computational stakeholders
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