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discoveries. Who You Are: Ph.D. with a proven track record of excellence in Computer Science and Machine Learning, with substantial domain experience in biology and genomics. Must have advanced at least one key
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the Sterne-Weiler Lab i n Computational Biology / Discovery Oncology and co-mentored by the Frey Lab in Prescient Design (Machine Learning for Drug Discovery). The postdoctoral position is focused
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antigens, T cell receptor (TCR) and antigen interactions and their crucial role in anti-cancer immune responses. You'll leverage your strong background in computational biology, machine learning, and
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apply cutting-edge machine learning algorithms, with focus on foundation models and LLMs/agents, to analyze complex biological data. This data includes gsingle cell genomics profiles, spatial data, and
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accelerate translational research. Build or leverage novel artificial intelligence and machine learning (AI/ML) techniques for advanced liquid biopsy (ctDNA) and tissue transcriptomic (RNA-seq) data to predict
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ATAC sequencing, spatial transcriptomics, proteomics, whole-genome sequencing, functional screens, bioinformatics, and/or data algorithms including machine learning will be given preference. A successful
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mammalian cell culture is preferred. Experience with or strong interest in learning computational structural biology approaches or cryo-ET is a plus. For information about the Deshpande Lab at Genentech
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on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws. If you have a disability and need an accommodation in relation to the online
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on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws. If you have a disability and need an accommodation in relation to the online
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on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws. If you have a disability and need an accommodation in relation to the online