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Field
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-generation AI models of gene regulation and disease progression. Our work is redefining Parkinson’s disease biology and enabling translational breakthroughs. The role Develop deep learning models across genome
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, a novel spatial discovery proteomics concept that integrates microscopic cell phenotyping with deep-learning based image analysis and global MS-based proteomics. This unique method was recently
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diseases, Genome Biology, 2024 S. Hudaiberdiev et al., Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits, PNAS, 2023 S. Li et
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, biomedical engineering, medical imaging, or related field Experience in deep learning with practical implementation Strong Python skills and relevant frameworks Experience with large clinical imaging datasets
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with Bayesian inference or machine learning is an advantage. • Proficiency in Python and/or R; experience with probabilistic programming (Stan, PyMC, NumPyro) or deep learning frameworks (PyTorch, JAX
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Director), head of the GIN's 'Brain, Behaviour and Neuromodulation' team. This multidisciplinary team brings together researchers, clinicians, engineers, PhD students and undergraduates around a common goal
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information, or quantum algorithms Knowledge of machine learning (e.g., deep learning, optimization, or learning theory) Programming skills in Python and experience with scientific computing (e.g., NumPy, SciPy
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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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programming and instrument control using Matlab, Python, Labview etc Machine / deep learning expertise Strong analytical skills and ability to work in a multidisciplinary team Excellent communication and
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new insights into the phenomena observed and enrich the databases required for deep learning methods. The neural networks currently being developed at LISTIC to detect and segment areas of movement in