We are seeking enthusiastic postdoctoral scholars in Computational Biology and Machine Learning. The successful candidate will develop integrative statistical and machine learning approaches for extracting insights from cutting-edge single cell omics (e.g. CITE-seq, scATAC-seq, spatial transcriptomics, TEA-seq) and multi-spectral imaging (e.g. CODEX, Vectra) datasets.
The candidate is expected to engage with the broader machine learning and computational biology communities by presenting work at top conferences, as well as publishing applications of new methods in high impact journals. This could be a good fit for someone with a strong machine learning background who wants to get domain-specific experience.
Candidates may be eligible to apply for the enhanced stipend and career development funding provided as a Hillman Postdoctoral Fellow for Innovative Cancer Research (details provided at hillmanresearch.upmc.edu/research/hillman-fellows/postdoctoral/ ).
Environment: The Osmanbeyoglu Lab www.osmanbeyoglulab.com/ is a multi-disciplinary hybrid wet/dry lab at the University of Pittsburgh. We are affiliated with the Department of Biomedical Informatics, Bioengineering, the Center for Systems Immunology and UPMC Hillman Cancer Center. Our projects are funded by NCI and The Fund for Innovation in Cancer Informatics (ICI). Our group is fortunate to have the necessary combination of large clinical sample volume at UPMC Hillman Cancer Center, single-cell technology and computational biology experience.
The University consistently ranks in the top 5 nationally for NIH biomedical research funding and the Cancer Center was recently ranked #7 by US News & World Report. Pittsburgh, PA is often voted the most livable city in the US featuring eclectic neighborhoods, diverse culinary and entertainment opportunities, as well as accessible outdoor recreation (www.coolpgh.pitt.edu/).
Up to $60,000 per year + excellent benefits
Ph.D. in applied quantitative disciplines, such as computational biology, bioinformatics, biostatistics, mathematics, or computer science with a strong interest in biomedical research. A strong computational background, proficiency in at least one programming language (e.g., R, MATLAB, Python) knowledge of statistics are also required. Ideal candidates would have publications demonstrating experience with code development, applied mathematics, machine learning, deep learning and/or computational biology. Experience with analyzing next-generation sequencing data would also be desirable, but is not essential. The candidate should 1) be able to work independently and as a member of a team, and 2) be hard-working, motivated, and eager to learn with an outstanding work ethic.
If interested, please send an email to Dr. Osmanbeyoglu (osmanbeyogluhu @ pitt dot edu) and include your CV (with references) and research interests. Please put the words “POSTDOC-APPLICATION-2021” in the subject line.