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. in genetics, cancer biology, computational biology, bioinformatics, computer science, systems biology, or a related field with relevant experience. Candidates from quantitative disciplines, including
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scalable software and algorithms for genomic inference Collaborate with researchers across statistics, genetics, and computational biology Contribute to manuscripts, presentations, and open-source software
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computational methods and tools, including prior experience with algorithms relevant to computational biology, is a plus. ● Ability to work independently as well as part of an interdisciplinary team in a
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advance pediatric, adolescent, and young adult cancer care using cutting-edge computational biology approaches. We strive to understand the germline genetics and tumor genomics of pediatric cancer to inform
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. Norbert Perrimon’s group in the Program of Genetics at Harvard Medical School. Perrimon lab is actively generating data sets of omics scale and this position will involve working with other post-doc
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Number: 16451 School: Harvard Medical School Position Description: We are seeking a highly motivated post-doc trainee to join Dr. Norbert Perrimon's group in the Program of Genetics at Harvard Medical
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Computational Biology group leads the computational biology efforts to characterize multi-omics sequencing datasets that describe the genetic changes that occur across breast cancer. This characterization is done
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involved in the bioinformatic and analytic aspects of predictive modeling. MINIMUM JOB QUALIFICATIONS: A Ph.D. in bioinformatics, genetics, statistics, mathematical, physical, or computer
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of Biomedical Informatics. This position will be funded through a grant supported by the NIH, INCLUDE (INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE) Project. The ideal
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, or related disciplines) Related Skills & Other Requirements Demonstrated abilities in mathematical modeling, analysis and/or scientific computation, scientific software and algorithm development, data analysis