491 computer-programmer-"https:"-"U"-"UCL" "https:" "https:" "https:" "https:" "https:" "P" uni jobs at Nature Careers in United States
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. Academic Clinician Track - Clinical responsibilities may include providing outstanding clinical care and productivity in program development as well as consultations for high-risk neonatology and maternal
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basic or translational research and the potential to develop an outstanding independent research program that supports the Institute's ultimate goal of harnessing the immune system to prevent and cure
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. Applicants must have: A medical degree or a terminal research degree (PhD or equivalent) in a relevant discipline. An actively funded research program in basic or translational research relevant to bladder and
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. Mentoring and resources will be provided to help the individual develop an independent research program and to facilitate the transition to an academic position. Application Instructions Please include
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of our product development teams building applications within the St. Jude Cloud ecosystem, including the large-scale data sharing application, Genomics Platform (https://platform.stjude.cloud
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Comprehensive Cancer Center. The successful applicant will be expected to develop an independent, externally funded research program in cancer immunology, cancer causing viruses, oncolytic viral therapies, cancer
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maintain an active, externally funded research program; to supervise graduate students in our Ph.D. program; and to teach undergraduate and graduate courses in their specific area of expertise as
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Glassdoor's "Best Places to Work". St. Jude is one of the best-funded research institutes in the US with an annual budget of over $2 billion per year (https://www.stjude.org/about-st-jude/financials.html). What
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spatial methods. A Ph.D. degree (or equivalent) is required. Successful candidates are expected to develop and sustain an externally funded research program. These positions are anticipated to begin in Fall
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implementing computational schemes for ODE and / or PDE based models Ideally experience with machine learning methods for identifying governing equations from experimental observations (e.g., https://github.com