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Together Knowledge, Qualifications, Skills and Experience Knowledge/Qualifications Essential: A1 PhD in a relevant subject area, or a veterinary degree registerable with the RCVS, or an equivalent
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Tenure Track in Sensory and Consumer Science at Department of Food Science, Aarhus University, De...
is focused on the interface between human senses and perception of food and contribute to designing healthy and sustainable food and beverage applications with high consumer acceptance. The position is
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this with expertise in high-performance computing and artificial intelligence using unique scientific infrastructures. Are you excited about working at the interface of natural and computer sciences? At
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for publication. To be successful, you will have a PhD in computational neuroscience, cognitive neuroscience, physics, applied mathematics or a related discipline. You will have research experience, ideally in a
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-augmented AI tools Interfacing AI tools with experimental facilities at CNM and Argonne Key Responsibilities Research leadership (50%) Develop and lead an independent and collaborative research program in
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and Individualized Medicine ; https://curatime.org/ ) a Clusters4Future initiative funded by the German Federal Ministry of Research, Technology and Space (BMFTR), integrating RNA technologies
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) Established Researcher (R3) Application Deadline 30 May 2026 - 22:00 (UTC) Country France Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not
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sequencing to study dynamic cell states in health and disease. The lab operates at the interface of engineering, biology, and medicine, combining rigorous experimental work with quantitative and computational
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courses. The person in this position will also mentor graduate students, contribute to interdisciplinary research initiatives, and enhance the visibility and impact of WSU’s Plant Pathology program. The
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project The main objective of this PhD project is to explore and analyze bio-inspired neural architectures for early detection from spatio-temporal data under realistic sensing and computational constraints