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are for 3.5 years. Scholarships also include up to $1,500 relocation allowance. Supervisor: Professor Matt Dun Available to: Domestic students PhD Eligibility Criteria The applicant will need to meet the
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The GW4 BioMed3 Doctoral Landscape Programme is offering up to 18 MRC funded studentships across a range of biomedical disciplines, with a start date of October 2027. These four-year studentships
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requirements for admission to the PhD programme Experience implementing and modifying deep learning architectures. Working knowledge of Python and a modern deep learning framework. Strong programming skills in
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100% 3-year PhD fellowship in chromatin and computational biology is available in the project group of Dr. Julia Madsen-Østerbye, research group of Prof. Philippe Collas, at the Division of Biochemistry
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2026 (or as agreed). Description of PhD Project The PhD student will be responsible for leading projects focused on the development of novel computational and AI tools to improve our understanding
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position A 100% 3-year PhD fellowship in chromatin and computational biology is available in the project group of Dr. Julia Madsen-Østerbye, research group of Prof. Philippe Collas, at the Division
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AITHYRA GmbH - Research Institute for Biomedical Artificial Intelligence of the Austrian Academy of Sciences | Vienna, Virginia | United States | about 6 hours ago
, together with our partners the TU Wien, Uni Wien and Meduni Wien, will start in September 2027. The goal of the PhD Program is to enable and empower AI/ML and life science students with the ability
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25 Sep 2026 Job Information Organisation/Company UNIVERSIDAD REY JUAN CARLOS (URJC) Research Field Other Researcher Profile Recognised Researcher (R2) Positions PhD Positions Application Deadline 2
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or more of the following areas: IoT, data mining, cloud/edge/fog computing. • Good knowledge in one of the following programming languages: C/C++, Python. Place of employment: Karlskrona. Employment level
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and artificial intelligence. An important component of the PhD will be determining which combinations of approaches are scientifically useful, rather than applying AI or other computational techniques