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of older persons. The candidate will also contribute to teaching activities related to machine learning or other areas depending on the candidate’s profile. Moreover, the candidate is a team player that
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main focus on our Computer-Aided Drug Discovery (CADD) platform. The successful candidate will work with a highly multidisciplinary team at VIB DS in close collaboration with a team of IT experts at VIB
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RNA-Seq, ChIP/DAP-Seq protein-DNA interaction data, bulk, and single-cell ATAC-Seq) and the application of diverse supervised machine learning approaches (e.g., feature-based, deep learning, and
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within the IN-DEEP project you will be at the forefront of developingnew hybrid machine learning (ML) accelerated solvers. A fast-expandingarea of research is the application of ML techniques to predict
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parts. First, the candidate will develop machine learning models to assist gynecologists and embryologists in their decisions and advice regarding couples with fertility problems. We will focus
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are currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning. In particular, we develop machine learning methods to derive
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are currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning. In particular, we develop machine learning methods to derive
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17 May 2024 Job Information Organisation/Company Royal Military Academy Department Defence Research Field Engineering » Mechanical engineering Engineering » Biomaterial engineering Researcher
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-2024-306 Is the Job related to staff position within a Research Infrastructure? No Offer Description We are seeking a motivated postdoctoral researcher to drive development of innovative machine learning
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quantitative approaches towards data science, including relevant developments in the field of geospatial data processing, photogrammetry, computer vision, and big data/machine learning. You have knowledge