51 phd-mathematical-modelling-ecological-modelling Postdoctoral positions at Yale University
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Computational Biology, Machine Learning and Deep Learning for Computational Biology, Computer Science, Applied Physics and Mathematics, or a related field. - Strong background in protein modeling, structural
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: We would like to recruit a postdoctoral fellow in cancer outcomes research, with a particular interest in decision/simulation modeling and cost-effectiveness analysis. The ideal candidate will have
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large amount of data, using advanced statistical techniques and mathematical analyses. Manage analytical projects from data exploration, model building, performance evaluation, through implementation
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. Studies incorporate approaches in both primary human immune cells and in vivo mouse intestinal model systems. Education and experience: Candidates must have a PhD or equivalent degree with a strong
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highly motivated to impact patient outcomes through translational approaches to the treatment of T cell malignancies. Experience with in vivo mouse immunotherapy models, protein/antibody engineering and
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modeling. However, interested candidates with a strong computational background and interest in getting involved in medical imaging and preclinical models are also strongly encouraged to apply. A PhD in
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positions) in the areas of privacy-preserving health data sharing, AI modeling and evaluation of medical and biological applications. The Postdoctoral Associate will be responsible for co-developing and
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), genome/phenotype analysis (Dr. Jihoon Kim) and applications of large language models (Dr. Ohno-Machado). The Postdoctoral Associate will be responsible for co-developing and conducting research projects
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the Pytorch library and running deep learning models. The successful candidate will work closely with a team of researchers and faculty members in the ClinicalNLP lab led by Dr. Hua Xu. More information of the
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Postdoctoral Associate — Bioinformatics and Data Science - Stites Laboratory The Stites laboratory utilizes a variety of computational, mathematical, and experimental methods to study problems in