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that do not have this background, are strongly motivated to acquire the relevant skills during the early phases of the PhD, supported by training and in close collaboration with experts in single-cell
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, computational biology, statistics or a closely related field. You have strong programming skills, preferably in Python, and experience with machine learning or deep learning. Experience in computer vision
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chapters, and shorter contributions such as blogposts. Some of these will be co-authored pieces with the principal investigator (Prof Van Calster), the postdoc and other team members. Contribution
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shorter contributions such as blogposts. Some of these will be co-authored pieces with the principal investigator (Prof Van Calster), the postdoc and other team members. Contribution to the outreach
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at least one deep-learning framework (PyTorch preferred).•A solid grounding in machine learning. Experience with representation learning, generative models, foundation models or multimodal integration is a
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considered a strong asset. Experience with Deep Learning and Artificial Intelligence is considered a plus. Excellent proficiency in the English language is required, as well as good communication skills, both
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: Master’s degree in Electrical Engineering Ranked within the top 10% of their class in MSc and BSc, and have exceptional grades Good background in deep learning with familiarity in model training, inference
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experience in Python and, more specifically, in common deep learning frameworks such as PyTorch and jax, for model training and inference have experience with embedded platforms such as FPGAs or RISC-V
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that truly understands its environment. You have a master's degree in Computer Science, Artificial Intelligence or similar. You are interested in Logic, Machine Learning, Knowledge Graphs, Stream
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, microscopy, spectroscopy, pore-structure characterization, geochemistry. You are interested in interdisciplinary research at the interface of materials science and microbiology and are motivated to acquire