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countervailing immunoediting processes that seek to control and eradicate these cancers. This project specifically focuses on ovarian cancer, a difficult-to-treat and life-threatening cancer for which early
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the following: Curriculum vitae Statement of research Two representative publications Two letters of recommendation Candidates may be asked to undergo an assessment as part of the interview process. Additional
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of the interview process. Additional Information: This is an immediate hire full-time term position through February 2027, with strong potential for reappointment based on funding and performance
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. Cross-Disciplinary Fellowships (CDF) are for applicants with a Ph.D. from outside the life sciences (e.g. in physics, chemistry, mathematics, engineering or computer sciences), who have not worked in
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dynamics, using an array of methods including natural language processing and experiments. This is a two-year position (one-year contract renewable based on performance). The primary criterion for acceptance
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statistics, computing, machine learning (ML), and genetics and genomics, with a focus on large-scale genetic, genomic, and phenotype data. The work will involve both methodological research and collaboration
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transcription machinery, and mRNA processing enzymes and their interactions with RNApII. We welcome applications from recent PhD graduates who are interested in these or related fields, particularly those who may
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dynamics, using an array of methods including natural language processing and experiments. This is a two-year position (one-year contract renewable based on performance). The primary criterion for acceptance
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collection and processing for lab and field based studies of back assisting wearable robots. The Research Fellow should be a collaborative problem solver who is proficient at building a strong rapport with
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-disciplinary team of researchers, including bioinformaticians, pathologists, oncologists, and computer scientists, and conduct original research on computational pathology. Digital pathology images contain rich