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to solve biomedical problems, or a PhD in biomedical sciences with a strong interest to apply AI and machine learning approaches. With our strong commitment to translating research findings to actionable
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include, but are not limited to, using the latest computational learning-driven approaches, including computational social science, foundation models and multimodal machine learning, to enhance
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(PhD, MD, or equivalent) conferred by the start date. Proven research and/or professional experience in machine learning and/or natural language processing, with a preference for prior experience working
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. Expertise in computational neuroscience software (e.g., MATLAB, Python) as well as statistical methods and statistical packages (e.g. SAS, R). Experience with machine learning methods is preferred
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decision making systems, in particular the use of different optimization, machine learning, and decision making modeling techniques for problem solving. Desire to grow collaborative research and mentorship
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learn and master various computer programs. Strong record of peer-reviewed publications. A PhD, MD or equivalent with prior relevant training in Immunology, Biology, Physiology, Biochemistry or related
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. Develop and apply ab initio computations, molecular dynamics simulations, and machine learning models. Collaborate with other researchers within the group and external partners. Present research findings
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principals to problem solve work. ● Ability to maintain detailed records of experiments and outcomes. ● Ability to quickly learn and master computer programs, databases, and scientific applications
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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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our team. We are looking for postdoc candidates to develop and apply cutting-edge technologies in spatial transcriptomics, single-cell sequencing, machine learning, and functional genomics