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Field
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Learning with a focus on in vitro fertilization (IVF) at Faculty of Technology and Society. Work duties Running cutting-edge research in Machine Learning (ML), focusing on Deep learning and on-device Large
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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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ability to formulate hypothesis and design effective experimental plans. High-level expertise in the required experiment or deep learning methods. Ability to initiate collaboration research in
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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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evaluate innovative methods based on generative models and Vision-Language Models. Design, implement, and validate deep learning approaches for vision applications. Publish research results in leading
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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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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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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
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). Deep learning has been used to perform this mapping from UAV (Batista et al., 2025; Chudasama et al., 2024; Lambert et al., 2025) or satellite imagery (Mattéo et al., 2021), at both very high resolution
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, training deep learning models on large satellite datasets, and contributing to the integration of forecasting workflows into the IceBox system. The candidate will work closely with an interdisciplinary team