Merck
Associate Scientist Postdoctoral Fellow - Computational Precision Genetics
Merck, Cambridge, Massachusetts, us, 02140
Associate Scientist Postdoctoral Fellow - Computational Precision Genetics
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Associate Scientist Postdoctoral Fellow - Computational Precision Genetics
role at
Merck .
Job Description Be a part of the legacy: Postdoctoral Research Fellow Program. Our Research Laboratories’ Postdoctoral Research Fellow Program aims to provide an academic focus in a commercial environment and position postdoctoral researchers to excel in breakthrough innovation.
Position Summary The Precision Genetics group in the Data, AI and Genome Sciences Department seeks a Postdoctoral Research Fellow to drive computational work on a translational project developing a reusable multi-omics and AI/ML framework to discover mechanism-based companion diagnostic (CDx) biomarkers that predict treatment response in autoimmune diseases.
Key Responsibilities
Analyze multi-modal pre- and post-treatment readouts, including epithelial barrier assays, cytokine profiling, single-cell RNA-seq, and spatial transcriptomics (e.g., 10x Visium, GeoMx, Stereo-seq).
Develop, benchmark, and maintain reproducible computational pipelines for bulk, single-cell, and spatial transcriptomics data processing (QC, alignment, cell-type annotation, and spatial analyses).
Implement multi-omic integration strategies combining spatial transcriptomics, single-cell expression, cell composition estimates, and genotype/SNP data.
Design, train, evaluate, and interpret AI/ML models (supervised and unsupervised) for predictive biomarker discovery and companion diagnostic candidate prioritization, emphasizing feature selection and model explainability.
Document methods, workflows, and results thoroughly; prepare and contribute to manuscripts, conference presentations, and IP/translation activities as appropriate.
Collaborate effectively with wet-lab scientists, clinicians, and computational colleagues, present results to the team and stakeholders.
Required Qualifications
Ph.D. or completion within 6 months in Computational Biology, Bioinformatics, Systems Biology, Genomics, Biomedical Engineering, Computer Science (with bioinformatics experience), or related discipline.
Demonstrated experience analyzing single-cell and/or spatial transcriptomics data (processing, clustering, differential expression, spatial analysis).
Strong programming skills in Python and/or R and familiarity with relevant libraries/tools (Seurat, Scanpy, Squidpy, Bioconductor, scikit-learn, PyTorch/TensorFlow).
Strong statistical skills and experience working with high-dimensional biological data; excellent data visualization abilities.
Excellent written and oral communication skills and evidence of productivity appropriate to career stage (publications, code repositories, or preprints).
Proven ability to work collaboratively in interdisciplinary teams and manage multiple projects concurrently.
Preferred Qualifications
Hands-on experience generating single-cell or spatial transcriptomics datasets from organoid models or close collaboration with teams that generate such data.
Familiarity with genotype/SNP data processing and integration (GWAS summary statistics, imputation, genotype–phenotype association analyses).
Experience with cloud platforms (AWS) and high-performance computing (HPC) environments.
Prior experience in translational biomarker discovery or developing clinically oriented predictive models.
Equal Employment Opportunity Statement As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status or other applicable legally protected characteristics. For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit EEOC Know Your Rights.
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Associate Scientist Postdoctoral Fellow - Computational Precision Genetics
role at
Merck .
Job Description Be a part of the legacy: Postdoctoral Research Fellow Program. Our Research Laboratories’ Postdoctoral Research Fellow Program aims to provide an academic focus in a commercial environment and position postdoctoral researchers to excel in breakthrough innovation.
Position Summary The Precision Genetics group in the Data, AI and Genome Sciences Department seeks a Postdoctoral Research Fellow to drive computational work on a translational project developing a reusable multi-omics and AI/ML framework to discover mechanism-based companion diagnostic (CDx) biomarkers that predict treatment response in autoimmune diseases.
Key Responsibilities
Analyze multi-modal pre- and post-treatment readouts, including epithelial barrier assays, cytokine profiling, single-cell RNA-seq, and spatial transcriptomics (e.g., 10x Visium, GeoMx, Stereo-seq).
Develop, benchmark, and maintain reproducible computational pipelines for bulk, single-cell, and spatial transcriptomics data processing (QC, alignment, cell-type annotation, and spatial analyses).
Implement multi-omic integration strategies combining spatial transcriptomics, single-cell expression, cell composition estimates, and genotype/SNP data.
Design, train, evaluate, and interpret AI/ML models (supervised and unsupervised) for predictive biomarker discovery and companion diagnostic candidate prioritization, emphasizing feature selection and model explainability.
Document methods, workflows, and results thoroughly; prepare and contribute to manuscripts, conference presentations, and IP/translation activities as appropriate.
Collaborate effectively with wet-lab scientists, clinicians, and computational colleagues, present results to the team and stakeholders.
Required Qualifications
Ph.D. or completion within 6 months in Computational Biology, Bioinformatics, Systems Biology, Genomics, Biomedical Engineering, Computer Science (with bioinformatics experience), or related discipline.
Demonstrated experience analyzing single-cell and/or spatial transcriptomics data (processing, clustering, differential expression, spatial analysis).
Strong programming skills in Python and/or R and familiarity with relevant libraries/tools (Seurat, Scanpy, Squidpy, Bioconductor, scikit-learn, PyTorch/TensorFlow).
Strong statistical skills and experience working with high-dimensional biological data; excellent data visualization abilities.
Excellent written and oral communication skills and evidence of productivity appropriate to career stage (publications, code repositories, or preprints).
Proven ability to work collaboratively in interdisciplinary teams and manage multiple projects concurrently.
Preferred Qualifications
Hands-on experience generating single-cell or spatial transcriptomics datasets from organoid models or close collaboration with teams that generate such data.
Familiarity with genotype/SNP data processing and integration (GWAS summary statistics, imputation, genotype–phenotype association analyses).
Experience with cloud platforms (AWS) and high-performance computing (HPC) environments.
Prior experience in translational biomarker discovery or developing clinically oriented predictive models.
Equal Employment Opportunity Statement As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status or other applicable legally protected characteristics. For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit EEOC Know Your Rights.
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