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models, in vivo fiber photometry, ex vivo slice physiology, chemogenetics, immunofluorescence, and/or intracranial pharmacological infusions Deadline to Apply 12/31/2026 Our University Community We value
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internationally recognised research environment. It is essential that you hold, or be close to completing, a PhD/DPhil in computational biology, mathematics, statistics, bioinformatics, oncology or another related
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, or master's level at the time of application. Proof of enrollment is required with your application. Students enrolled at institutions outside the U.S. and its territories are ineligible. For undergraduate
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continue to live and breathe this spirit today, not because it’s simply ‘the right thing to do’ but for what it helps us achieve and the intellectual brilliance it delivers. We continue to embrace diversity
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and breathe this spirit today, not because it’s simply ‘the right thing to do’ but for what it helps us achieve and the intellectual brilliance it delivers. We continue to embrace diversity of thought
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 19 hours ago
response. Ask someone whose judgement you trust to proofread it and make suggestions for improvement. Efficient writing is valued over quantity of writing. Submitting the application -- we can’t select you
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the development of proposals and identifying funding opportunities. Participate in departmental seminars, workshops, and other events, engaging with the academic community. Qualifications: Doctoral degree (or near
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disciplinary boundaries towards bioinformatics and computational biology. You do not need to arrive as an expert in both fields. This is what you will do You will develop quantum-algorithm prototypes within
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education and research worldwide. The driving force behind the faculty’s success is its robust research profile combined with the energy and creativity of its student body and academic community. It is
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research teams: 1) The AI Group: Experts in systems, control, optimization, Large Language Model (LLM) training, domain adaptation, and instruction tuning, agentic AI orchestration, and reinforcement