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) Investigate the role of key transcription factors in regulating hematopoiesis in conditional knockout and knockin mouse models. Candidates should have obtained a PhD or an MD/PhD degree and research training in
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laboratory meetings, project discussions, and scientific presentations. Maintain compliance with institutional biosafety, animal care, and research regulations. Qualifications Qualifications PhD in Immunology
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for nanofabrication of quantum devices. You will join a diverse and enthusiastic team of academic staff, PhD students and postdocs in the Steele Lab in the Quantum Nanoscience Department in Delft. You will meet
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of Position Temporary Position Time Status Full-Time Required Education PhD or PsyD Required Related Experience Completion of APA-Accredited Internship Required License/Registration/Certification None Physical
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Appointment Staff - 12 month Position Pension Eligibility ABP Qualifications Minimum Education and Experience PhD, MD, or equivalent doctoral degree in Neuroscience, Biomedical Engineering, Psychology
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 6 hours ago
motivated candidate with a strong interest in machine learning and clinical neuroscience. The lab studies resilience and vulnerability in brain aging and dementia, and builds computer-aided methods and tools
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routinely collected healthcare data. Through the analysis of linked electronic health records, you will generate evidence to inform clinical guidelines, optimise prescribing practices and support healthcare
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approximately EUR 2 500 per month), the salary is fixed as an hourly rate Bonus payments for articles in high impact journals, supervised PhD and MSc thesis, awarded and managed public and private competitive
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, pumps, valves operated by a computer and the corresponding software Develop flow cells to connect various spectroscopic tools to the setup Create and validate reproducible automated workflows
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across specialties, linking clinical care and research; (2) supporting the development of predictive models for dental disease outcomes using structured and unstructured electronic health records; and (3