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on energy-efficient circuit design and software-hardware co-optimization, with exciting applications in graph-based prediction. What we’re looking for: A PhD in Electrical and Computer Engineering or a
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. This will include: Developing spatial community detection tools to identify functional hubs and cellular ecosystems in tissue. Implementing dynamic modelling frameworks, combining agent-based models and graph
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duration of 24 months. Where to apply E-mail natjecaji.pisarnica@irb.hr Requirements Research FieldPhysicsEducation LevelPhD or equivalent Skills/Qualifications PhD in physics, research experience in
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for candidates to have the following skills and experience: Essential criteria PhD in bioinformatics, computational biology, or a related discipline Extensive experience and expertise in applying/developing and
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science Mathematics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 22 Oct 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Hours Per
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Stig Brøndbo 22nd October 2025 Languages English English English Faculty of Science and Technology PhD Fellow in Knowledge-Driven Machine Learning Apply for this job See advertisement The position A
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, acknowledging receipts of proposals, and maintaining a system to track proposals. Evaluate and perform preliminary analysis of the data using graphs, charts or tables to highlight the key points of the research
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research directions include: Reversible material representation methods for accelerated inverse design Large language, diffusion & graph neural models for materials discovery Fine tuning and architecture
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Australian National University | Canberra, Australian Capital Territory | Australia | about 1 month ago
at the John Curtin School of Medical Research (JCSMR), within the ANU College of Science and Medicine. This role will lead the development of advanced deep learning frameworks—including graph neural networks
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knowledge graphs, rules, and process understanding, with implications across sectors from ecology to infrastructure. 4. Theme 4 (“Communities”): Green and Resilient Communities and Entrepreneurship