Senior Scientist (Computational Genomics & Large-Scale Molecular Data Analysis)(Dr Sealfon's Lab) - Neurology
About The Position
The Senior Scientist in Dr. Sealfon’s Lab in Neurology will lead computational analysis of high-dimensional datasets and work closely with a computational-experimental team to generate biological insights from complex genomic data. The role focuses on single-cell transcriptomics and epigenomics, large-scale datasets, and quantitative and programming approaches, with machine learning and AI experience considered highly desirable. The position includes analyzing single-cell and multiomic data, integrating results across modalities and cohorts, developing processing pipelines for novel single-cell technologies, and applying statistical and machine-learning methods to characterize cellular states, regulatory programs, and epigenetic signatures. The Senior Scientist will also present findings internally, contribute to publications and grant applications, stay current with emerging methodologies, and perform other related duties.
Requirements
- Ph.D. in a science or related field, such as Computational Biology, Bioinformatics, Genomics, Statistics, or Computer Science.
- At least five years of experience with scientific investigation.
- Demonstrated outstanding achievement in a field of research.
- Contributions to peer-reviewed publications, inventions, or similar work, at least some of which had a major impact on advancing the field or discipline.
Nice To Haves
- Prior experience successfully securing external grant funding.
- Strong experience analyzing bulk and single-cell RNA-seq and epigenomic data.
- Proficiency in R, including common single-cell analysis frameworks.
- Experience working with large-scale genomic datasets and high-performance computing environments.
- Strong statistical background and data visualization skills.
- Experience analyzing DNA methylation data using array-based or sequencing-based approaches.
- Experience analyzing long-read RNA sequencing datasets.
- Demonstrated use of machine-learning or AI methods for genomic data integration or prediction.
- Familiarity with cloud-based workflows and reproducible pipeline development.
- Track record of publications in peer-reviewed journals.
Responsibilities
- Lead analysis of single-cell RNA-seq and multiome datasets, including joint RNA/ATAC profiling.
- Perform integrative analyses across modalities, including bulk RNA-seq, ATAC-seq, and DNA methylation datasets.
- Develop processing pipelines for novel single-cell multiomic technologies.
- Apply statistical modeling and machine-learning methods to identify cellular states, regulatory programs, and epigenetic signatures.
- Design and implement integrative multi-omic analyses across cohorts and experimental systems.
- Present findings internally and contribute to publications and grant applications.
- Stay current with emerging single-cell and AI-driven genomic analysis methodologies.
- Perform other related duties.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
