9 machine-learning "https:" "https:" "https:" "Universiteit van Amsterdam" Fellowship positions at Genentech
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intelligence (AI) residency) to advance scientific machine learning for clinical oncology. The project builds a hybrid framework that couples an existing quantitative systems pharmacology (QSP) model of cancer
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scientific conferences and publish models and scientific insights in high-impact journals Who You Are: Ph.D. in Computational Biology, Bioinformatics, Computer Science or Machine Learning related field
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a pioneer, harnessing state-of-the-art Omics technologies to dissect fundamental biological mechanisms, power large-scale supervised and foundational machine learning initiatives, and comprehensively
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collaborative and multidisciplinary environment. Previous experience with proteomics is not required. To learn more about the Ori Lab, please see link below: https://www.gene.com/scientists/our-scientists
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laboratory experiments Working knowledge of biochemical techniques is a plus. For information about the Vucic lab at Genentech, please go to: https://www.gene.com/scientists/our-scientists/domagoj-vucic https
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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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communication skills, with the ability to present complex data to varied audiences. ● A collaborative mindset and the ability to work effectively in an interdisciplinary team environment. To learn more about the
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of bioinformatics and computational analysis. To learn more about the Dey Lab, please visit the link below: https://www.gene.com/scientists/our-scientists/anwesha-dey The expected salary range for this position based
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-Coding Genome Edits: Develop innovative machine learning approaches for designing precise non-coding genome edits, focusing on how non-coding alterations influence gene regulation and cellular function