75 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" positions in Belgium
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intelligence, machine learning and data science. You will play an active role in the research team, publish papers, take part in workshops, public events and other activities. The candidates should have a
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
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» OtherEducation LevelPhD or equivalent Skills/Qualifications Who you are PhD in Computer Science, Machine Learning or related field or 5+ years of relevant industrial experience. Strong track record of developing
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to communicate the accomplished / in-process work to internal and external stakeholders and adapt directions where needed. Where to apply Website https://www.imec-int.com/en/work-at-imec/job-opportunities/machine
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Infrastructure? No Offer Description The PhD candidate will work on the development of advanced statistical and machine learning methods for time series prediction, with applications mainly in the field of traffic
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: Shape the future of immersive visual technologies through optical, computational, and machine‑learning innovation. We are a university research group at imec-VUB in Brussels, with expertise in optical
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the top 10% of their class in MSc and BSc, and have exceptional grades; should have a background in microwave engineering and machine learning; should have strong communication skills and be fluent in
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. ETRO, the Department of Electronics and Informatics (http://www.etrovub.be/) of the Vrije Universiteit Brussel (VUB), performs fundamental and applied research in signal processing, AI, computer vision
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with Machine Learning Highly motivated to learn about biology and (the study of) biological data Enthusiastic team player Desirable but not required Experience with single-cell omics data Experience with
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of thermal energy and (hybrid) machine learning in which physics-based models are combined with data-driven techniques. Thermal cycles make it possible to meet the demand for heating, cooling, and electricity