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knowledge in bioinformatics, machine learning, statistics and programming skills (R, Python, or MATLAB) are required. The ideal candidate should demonstrate a record of publications in the area. Knowledge in
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would include: Co-developing a hybrid machine learning/process-based model of anaerobic digestion processes Performing techno-economic and lifecycle analysis of microgrids build around novel biogas-fueled
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resulting from T regulatory (Treg) cells by conducting genetic screens to overcome this suppression and to enhance CAR T cells for lymphoma. On the other hand, we also seek to apply the lessons learned from
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traditional 2D geological maps into complex 3D structures by harnessing state-of-the-art data science and machine learning techniques at large scales. The research will use geophysical, geochemical, and
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conferences, and contribute to open-source tools. Collaboration with clinicians, data scientists, and machine learning experts will be an essential and enriching component of the position. Strong candidates