Postdoctoral Research Position in Statistical Genetics and Genomics

Harvard University; Boston (MA); On-site; USD 68,000 - 83,000; Full time

Job summary

Harvard University in Boston invites applications for a Postdoctoral Research Fellow in Statistical Genetics and Genomics. The successful candidate will develop and apply statistical, machine learning, and AI methods to large-scale genetic and phenotypic data under the supervision of Dr. Xihong Lin in the Department of Biostatistics, Harvard T.H.

Chan School of Public Health. The position emphasizes methodological research and collaboration with researchers in NIH consortia, with focus on large

Qualifications

• Ph.D. in a quantitative field with strong research background in statistics and ML.
• Strong background in statistics, ML, programming, and data analysis.
• Genetics/genomics knowledge and good written and oral communication skills.

Responsibilities

• Develop and apply statistical, ML, and AI methods for analysis of large-scale genomic and phenotype data.
• Collaborate with investigators in NIH consortia and subject-matter researchers.
• Work with large datasets including whole-genome sequencing, biobanks, single-cell and CRISPR multiome data.

Skills

Statistics

Computing

Machine Learning

Genetics & Genomics

Programming

Data Analysis

Education

Ph.D. in statistics/biostatistics/computer sciences/computational biology

Job description

Postdoctoral Research Position in Statistical Genetics and Genomics

Title Postdoctoral Research Position in Statistical Genetics and Genomics

School

School Harvard T.H. Chan School of Public Health

Department/Area

Position Description

Postdoctoral Research Fellow position in statistical genetics and genomics is available at the Department of Biostatistics Harvard T. H. Chan School of Public Health. This position will be supervised by Dr. Xihong Lin (https://www.hsph.harvard.edu/lin-lab/ ), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods for analysis of large-scale whole genome genetic and genomic and phenotype data. Examples include large Whole Genome Sequencing association studies, biobanks, single-cell and CRISPR multiome data, integrative analysis of genetic and genomic data, causal mediation analysis and Mendelian Randomization, polygenic risk scores, and AI/transformer-powered analysis. We seek an individual with strong backgrounds in statistics, computing, machine learning (ML), and genetics and genomics, with a focus on large-scale genetic, genomic, and phenotype data. The work will involve both methodological research and collaboration with subject matter researchers and investigators in large NIH consortia.

Basic Qualifications

Ph.D. in a quantitative field, e.g., statistics or biostatistics, computer sciences, computational biology, strong research background in statistics and ML, programming, data analysis, strong genetic and genomic knowledge, as well as good written and oral communication skills.

Additional Qualifications

Salary Range

$75,000/year

Minimum Number of References Required

Minimum Number of References Required 3

Maximum Number of References Allowed

Maximum Number of References Allowed 4

EEO/Non-Discrimination Commitment Statement

Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard’s academic purposes.

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Supplemental Questions

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