Postdoc: ML for Single-Cell & Spatial Genomics

University of Virginia; Charlottesville (VA); Sur place; USD 50 000 - 65 000; Plein temps

Résumé du poste

The University of Virginia is seeking a Postdoctoral Researcher in computational biology and machine learning within the Chu Lab, Department of Genome Sciences. This role involves leading projects on spatial transcriptomics and developing novel machine learning frameworks to analyze biological data.

Successful candidates will have a Ph.D. in a relevant discipline and demonstrate a strong foundation in mathematics and statistics. This position offers a collaborative mentorship environment and supports scientific independence during research. The lab is situated in a vibrant academic community in Charlottesville, Virginia.

Qualifications

• Candidates must have a Ph.D. in a relevant quantitative discipline by the appointment start date.
• Prior experience with spatial transcriptomics or single-cell omics is a plus, but not required.
• Strong desire to work on biological problems through quantitative methods.

Responsabilités

• Develop models for spatial and single-cell transcriptomics.
• Build generative models to characterize cellular and tissue heterogeneity.
• Develop deep-learning and statistical methods for gene regulation analysis.

Connaissances

Strong foundational knowledge in mathematics and statistics

Proficiency in PyTorch

Intellectual curiosity for solving biological problems

Formation

Ph.D. in Computer Science, Applied Mathematics, Statistics, Computational Biology, or related fields

Description du poste

The University of Virginia is seeking a Postdoctoral Researcher in computational biology and machine learning within the Chu Lab, Department of Genome Sciences. This role involves leading projects on spatial transcriptomics and developing novel machine learning frameworks to analyze biological data.

Successful candidates will have a Ph.D. in a relevant discipline and demonstrate a strong foundation in mathematics and statistics. This position offers a collaborative mentorship environment and supports scientific independence during research. The lab is situated in a vibrant academic community in Charlottesville, Virginia.