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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. Demonstrated experience with large
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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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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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initio computations, molecular dynamics simulations, and machine learning models. Collaborate with other researchers within the group and external partners. Present research findings at conferences and
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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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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
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Affairs. The FY25 minimum is $73,800. A fully funded postdoctoral fellowship is available in the Ophthalmic Microsystems Laboratory at Stanford, which is led by Charles DeBoer, MD, PhD in the Department
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, mathematics, physics, or a related field. The ideal candidate should demonstrate a record of publications in the area. Strong knowledge in machine learning, statistics and programming skills (R, Python
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research programs. Required Qualifications: o Highly motivated postdoctoral researcher with: • Experience in relational databases, big data curation and analysis • Expertise in machine learning, including