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Field
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scalable deployment Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches Design and run experiments using the latest ML tools and frameworks
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200 people, working in four divisions: Algorithms, AI & Data Science, Software, and Interaction. The atmosphere is collegial and informal. You will join the Human-Centred Computing group
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on ML algorithms for lifetime estimation (GNNs). We are part of the Acoustics & Vibration Research Group itself part of the Department of Mechanical Engineering, Faculty of Engineering of the Vrije
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microscopy and atom probe tomography will be prepared. Finally, you will merge the images by means of deep learning algorithms. Your tasks in detail Development of the experimental protocol for the imaging
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, Microbiology, Evolutionary Biology or equivalent Practical experience with bacterial cultivation techniques (familiarity of BSL-2 biosafety protocols) Proficient in working under sterile conditions Ideally
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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to muon g-2 from lattice Quantum Chromodynamics and algorithmic developments for multi-level and RG-improved simulations (research group of Urs Wenger) C.) Study of multi-hadron systems, with a focus on
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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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interact in a polite and professional manner. Support: You will work with a PDRA alongside PhD students and overseen by an experienced academic. The group work in the broader Ecology and Evolutionary Biology
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Evolutionary Biology Division. They will join weekly lab meetings held jointly between five research groups covering a broad range of ecology. They will work in the Lyle laboratory alongside MSc Entomology