Postdoctoral and Graduate Positions at the Genomic Signal Processing Lab
We invite applications for postdoctoral scholars and graduate students to join our Genomic Signal Processing Lab to work on our five-year
National Cancer Institute (NCI) Physical Sciences in Oncology U01 project on "Multi-Tensor Decompositions for Personalized Cancer Diagnostics and Prognostics."1
The Genomic Signal Processing Lab is widely recognized for breaking new ground in mathematics, genetics, and at the interface between the two fields, since our highly cited invention of the "eigengene." We pioneered both matrix and tensor modeling of large-scale molecular biological data, and demonstrated that they can be used to correctly predict previously unknown cellular mechanisms. Postdoctoral and Ph.D. alumni of our lab have gone on to faculty positions at major universities and data science leadership positions at pharmaceutical companies and financial institutions.
The postdoctoral scholars and graduate students will participate in (i) the development of new mathematical frameworks that generalize the singular value decomposition (SVD) from one two-dimensional dataset to multiple high-dimensional datasets; (ii) the use of these frameworks in the computational modeling of patient-matched genomic profiles from, e.g., the Cancer Genome Atlas (TCGA); and (iii) the experimental testing of the models in collaboration with our colleagues from the University of Utah School of Medicine. This work is expected to offer answers to the open question of the relation between a tumor's genome and a patient's outcome.
Successful postdoctoral applicants will have (i) a Ph.D. in applied mathematics, bioengineering, physics, or a related discipline, (ii) with research, possibly also work experience in data science, preferably also scientific computing and genetics, and (iii) a track record of published papers and conference presentations. To apply for a postdoctoral position, please e-mail your CV, including the contact information for three references, to Orly Alter.
Successful graduate applicants will have (i) a B.Sc. or an M.Sc. in applied mathematics, bioengineering, physics, or a related discipline, (ii) some additional background in genetics, and (iii) some research or work experience in data science, preferably with a track record of published papers or theses, or conference presentations. To apply for a graduate position, please submit your application for graduate studies at the University of Utah Department of Bioengineering2 in the Track in Data Science and Computation.3
The University of Utah is one of the most innovative institutions in bioengineering, computer science, and human genetics. Beautiful, cosmopolitan, and with a large population of young professionals, Salt Lake City offers easy access to internationally renowned ski resorts and national parks.