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-relationships, materials optimization, materials under extreme conditions, and generative AI. Candidates must possess substantial experience in artificial intelligence and machine learning methods, specifically
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cutting-edge genomics and computational analyses to investigate transcriptome, epigenome and chromatin architecture. Learn more: Our benefits , where we prioritize your well-being and success to enhance
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. The role will also provide the opportunity to learn and develop skills in structure-based drug design. The role is ideal for someone who has, or is about to be awarded, a PhD in structural biology and would
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for secondments in one of the collaborating institutions and/or to co-supervise a PhD student. A secondary affiliation to EPFL or UoE may be offered to candidates with the appropriate profile. Appointment is
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Post-doctoral Fellow/Senior Research Assistant in the Centre for Information Technology in Education
of Education (Ref.: 533113). To commence from as soon as possible to 31 August 2027 Applicants should possess a doctoral or master’s degree in Education, the Learning Sciences or a related discipline, with a
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operate experimental facilities (electrolysis, PCM, BESS, etc.) and develop tools related to PtX testing, modelling, control, and energy system integration Co-supervise BSc, MSc, and PhD students and
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biology and FLASH/ultra-high dose rate radiotherapy (UHDR-RT). This position offers an exceptional opportunity for a motivated PhD or MD/PhD scientist to advance the biological and translational foundations
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based courses at the bachelor, master, and PhD levels in Arctic Biology, Geology, Geophysics, Technology and Safety. UNIS exploits its year round presence in the unique Arctic environment, utilising
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more effective screening and therapy. The postholder will focus on developing and applying advanced computer vision and machine learning methods for multimodal imaging and real-time analysis in
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the outcomes of SCC surgery. Job Responsibilities: As a PhD candidate, you'll focus on: Develop cutting-edge AI models: Train state-of-the-art deep learning models to segment SCC and healthy tissues using both