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our research program, see https://meyer-lab-cshl.github.io/ Position Responsibilities The successful candidate will study tolerance induction and generation of diversity in the immune system as part of
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are expected to have a PhD in Physics, Mathematics, Computer Science or a related quantitative discipline. Ideal candidates from the biological sciences should have experience with scientific programming. Ideal
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Biology and Artificial Intelligence PhD program . CSHL also has partnerships with nearby Stony Brook University and with the Zucker School of Medicine at Hofstra University in affiliation with Northwell
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educational institution located on the North Shore of Long Island, New York. The highly ranked School of Biological Sciences at CSHL trains PhD students, including through a recently launched BioAI PhD program
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Requirements Position Requirements: EDUCATION: · Bachelor’s degree in Computer Science, Information Security, or a related field. (Masters Preferred) · Certification(s) in one or more of the following areas
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of the on-premises and cloud environment at CSHL including roadmap development and actively pursues development of the team and resources to support computationally-driven science. The person in this role keeps
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new topics and approaches are paramount. The ability to positively interact with other group members while being individually productive is also required. Position Requirements PhD degree in Analytical
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PhD in biomedical sciences Experience/Skills: Ideal candidates should have strong research backgrounds in molecular and cellular biology, animal model and cancer research, and experiences with flow
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have completed PhD training in biomedical sciences, preferably in immunology, metabolism, cancer biology, epigenetics or microbiology. We are looking for an experienced and highly motivated scientist
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scientific discoveries. PhD candidates expecting to complete by 2024 are encouraged to apply. Candidates with expertise in organic synthesis, peptide/ natural product/macrocycle chemistry, or chemical biology