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pipelines for processing RNA-seq, single-cell RNA-seq, genomics, and proteomics data. Develop novel algorithms and integrated data visualization applications when existing software packages are not available
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. The selected candidate will contribute to one or more research projects within the Systems Genetics group led by Professor Enrico Petretto (Principal Investigator). These project(s) will be conducted
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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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methods for additive manufacturing applications, including ANNs and evolutionary genetic algorithms for process optimization supported by programming knowledge (e.g. Matlab, Python). Hands-on experience
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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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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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the cellular and molecular pathways disrupted in brain disorders such as schizophrenia and autism, by utilizing recent advances in genetics and genomics. We are developing and applying tools to understand how
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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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Dr Maria Secrier and be embedded within the dynamic and collaborative research environment of the UCL Genetics Institute. The position offers a unique opportunity to work at the interface of cancer
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3 – Quantum algorithms for data clustering: Clustering algorithms are of fundamental importance when dealing with large unstructured datasets and discovering new patterns and correlations therein