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Position: Sr. Scientist, Immunoinformatics, Oncology Bioinformatics
Institution: Moderna, Inc.
Location: Cambridge, Massachusetts, United States
Duties: Design, implement and evaluate leading-edge machine learning methods related to cancer immunotherapy; Explore large-scale immunological datasets, including genomic, transcriptomic, mass spectrometry, and structural data, to derive and integrate orthogonal contributors of effective immunotherapy design; Stay abreast of scientific findings and technological developments and continuously improve computational methodology; Maintain detailed documentation of data analysis methods and results; Present findings and participate in cross-function team meetings
Requirements: PhD degree in Computational Biology, Bioinformatics, Computer Science, or a related field + 2 years of relevant experience, or MS degree + 5 years of relevant experience; Strong track record in machine learning algorithm development, preferably with applications in immunology, genomics, or personalized medicine; Proficiency in handling and interpreting large-scale biological datasets, including genomic and proteomic data; Strong programming skills in Python/R and with ML frameworks (e.g. PyTorch)
   
Text: Sr. Scientist, Immunoinformatics, Oncology Bioinformatics Design, implement and evaluate leading-edge machine learning methods related to cancer immunotherapy; Explore large-scale immunological datasets, including genomic, transcriptomic, mass spectrometry, and structural data, to derive and integrate orthogonal contributors of effective immunotherapy design; Stay abreast of scientific findings and technological developments and continuously improve computational methodology; Maintain detailed documentation of data analysis methods and results; Present findings and participate in cross-function team meetings PhD degree in Computational Biology, Bioinformatics, Computer Science, or a related field + 2 years of relevant experience, or MS degree + 5 years of relevant experience; Strong track record in machine learning algorithm development, preferably with applications in immunology, genomics, or personalized medicine; Proficiency in handling and interpreting large-scale biological datasets, including genomic and proteomic data; Strong programming skills in Python/R and with ML frameworks (e.g. PyTorch)
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