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for drug target discovery, computational biology, advanced bioinformatics, and novel AI algorithms for identifying drug targets in complex diseases such as chronic kidney disease, idiopathic pulmonary
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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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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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. 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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bioinformatics, computational biology, biology, genetics, computer science, statistics, applied mathematics, physics or a related field. Strong programming skills in Python, R, C/C++ or similar, with experience
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transportation contexts, and machine learning classifiers Heuristics & Solvers: Develop and refine custom heuristics and metaheuristics (e.g., Tabu Search, Genetic Algorithms) to find high-quality solutions
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‑growth opportunities. Your qualifications should include: Ph.D. in computer science, bioinformatics, computational biology, genetics, or a closely related quantitative field. A degree in computer
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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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validate a comprehensive genetic panel for the molecular diagnosis of pituitary diseases. Using next-generation sequencing (NGS) technologies and a bioinformatics algorithm, the panel will identify genetic