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inflammation, multiparameter flow cytometry, and bioinformatics/computational biology is desired. Please send curriculum vitae, three names of reference and a one-page summary of research background and
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in residence for duration of appointment; during appointment revise doctoral dissertation or complete research project resulting in publishable manuscript; provide one lecture as part of the CEAS
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Postdoctoral position in AI for protein design with applications to TCR & BCR models The lab of Prof. María Rodríguez Martínez at the Department of Biomedical Informatics & Data Science, Yale School
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at national/international conferences Access to a broad network of collaborators at Yale and beyond Qualifications We welcome applicants with backgrounds in either experimental biology, computational biology
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(SUDs), psychiatric conditions, and other behavioral and lifestyle characteristics that impact human health using large datasets and biobanks including the Million Veteran Program (MVP), the SUD working
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in preclinical PET/CT or PET/MR imaging and kinetic modeling. A PhD in biomedical engineering, physics, or a related field is required. However, interested candidates with a strong computational
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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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: ● Completed doctorate in Biostatistics, Statistics, Data Science, Computer Science, Bioinformatics, or a related field before the start of the appointment ● Strong oral and written communication skills
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where it would be cost-effective to screen and (iii) incorporating multi-omics data to better identify at-risk individuals beyond lifestyle and environmental approaches alone. Our research program has
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Association and Yale Office for Career Strategy. Qualifications Candidates should have or be close to obtaining a PhD in either genetics, genomics, computational biology, bioinformatics, or a related field