1,295 machine-learning "https:" "https:" "https:" "https:" "The Open University" positions at Nature Careers
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. AT-CERE is closely connected with the center CERE of DTU (www.cere.dtu.dk ) and KT Consortium (https://www.kt.dtu.dk/research/kt-consortium ) which is a cross-disciplinary and cross-center activity of
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(2014). https://doi.org/10.1126/science.1253920 [2] An RNA origami robot that traps and releases a fluorescent aptamer. Science Advances (2024). https://doi.org/10.1126/sciadv.adk1250 Your qualifications
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. Interdisciplinary research is actively promoted by the Faculty of Science, fostered under the University-wide six Interdisciplinary Labs (https://interdisciplinary-research.hkbu.edu.hk/), and supported by state
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. Describe a deep learning project you have executed. Projects in computer vision for microscopy image analysis are especially relevant. Include a link to a code repository if possible. If you contributed to a
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Tenure Track in Sensory and Consumer Science at Department of Food Science, Aarhus University, De...
aligned to the Science Team ‘Food Quality Perception and Society’ (FQS) at the Department of Food Science http://food.au.dk/en/foodresearch/science- teams/food-quality-perception-society/. The Science Team
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Institute at VTC (FBRI - https://fbri.vtc.vt.edu/ ) for a tenured or tenure-track faculty position at the associate or full professor level. The research institute supports entrepreneurial activity through
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-body physics nonequilibrium quantum dynamics, to quantum computation, quantum information, and machine learning. The Institute provides a stimulating environment due to an active in-house workshop
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if they demonstrate strong relevant skills. Coursework or strong background in computational mechanics / FEM, numerical methods, and scientific programming. Exposure to machine learning / data-driven modelling and/or
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. Describe a deep learning project you have executed, ideally a creative use of supervised fine tuning of a pre-trained vision transformer, U-Net architecture, or related topic. Projects in computer vision for
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to investigate the uterine endometrium and maternal-fetal interface, with the goal of improving female and fetal health. More information about the lab and their work can be found by visiting https