460 machine-learning "https:" "https:" "https:" "https:" "The Open University" positions in Belgium
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Where to apply Website https://jobs.vito.be/o/phd-position-coupling-electrochemical-nitration-and-redu
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such as ground and aerial vehicles, and mobile robots. This includes: formulating and solving long-standing multiterminal information theory problems using modern machine learning techniques; designing and
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, optimization, and continuous learning in a rapidly evolving field.Desirable: experience with multi‑omics datasets, single‑cell or spatial technologies, or basic scripting skills (R/Python). Our offer Access
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development, optimization, and continuous learning in a rapidly evolving field. Desirable: experience with multi‑omics datasets, single‑cell or spatial technologies, or basic scripting skills (R/Python). Our
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, proteomics, microscopy, structural biology, technology development, and bioinformatics at VIB-UAntwerp Center for Molecular Neurology (https://cmn.sites.vib.be/ ), at VIB (https://vib.be/ ), and at UBirmingham
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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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research groups within CCB (Learn more: Bioinformatics & AI ). Your Role We are seeking a skilled computational biologist to organize and deliver training on bioinformatics and AI for the CCB research
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contribute 1) to the analysis methods and metrics for understanding the complex interactions between forage resource and dynamics; 2) to develop Machine Learning methods for analysing sensor data on animal
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interdisciplinary work at the interface between neurodegeneration, modeling, screening and machine learning Prior experience in iPSC modelling and CRISPR tools Our Offer A stimulating, international
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such as surgery, patient or staff scheduling using, e.g., multi-objective optimization or machine learning approaches and analyzing efficiency-fairness trade offs. The research will be conducted under