Postdoctoral position in ML/CompBio, UPenn.
We are looking for a capable postdoc with strong ML background to join the BioCiphers lab at UPenn. The lab belongs to both the department of Computer Science at the Engineering school, and the department of Genetics in the Medical school.
About the position:
Candidates should have a good background in probabilistic graphical models, approximate inference, statistical learning, and Bayesian inference in generative /discriminative setting. Recommendation letters are important. Experience in analyzing large volumes of data is good to have. Background in computational biology and experience with biological datasets are desirable but not required.
About the BioCiphers lab:
We combine diverse sources of high-throughput genomic/genetic data to build predictive models for RNA processing. We also have a wet lab component that allows us to verify predictions, improve our models, etc. We focus on (a) basic understanding of RNA biogenesis (b) disease applications. Working within one of the top medical schools in the US gives us access to unique data, resources, and world experts to collaborate with. The lab was only recently established and includes a small lively group of people from diverse backgrounds.
See more details at: http://www.biociphers.org/
Applicants should email firstname.lastname@example.org with the title “Postdoc Application” and include a cover letter, a CV, and a list of at least two references.