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Field
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Science, or a closely related field Prior coursework and working experience in data science, machine learning, statistics, or related areas Proficiency in Python for data analysis and modeling, machine learning
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., statistical modelling, Artificial Intelligence/Machine Learning) Experience in computational biology and bioinformatic analysis Proven ability to write detailed, technically accurate reports on complex research
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/ computer vision and pattern recognition, including but not limited to biomedical applications Strong interest in applied machine learning, including but not limited to deep learning Experience utilising GPU
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. You will contribute to developing datasets, baseline models, personalized learning engines, reasoning-graph representations, cross-domain mapping algorithms, and RLHF-style feedback loops that improve
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systems Experience in deep learning, computer vision, or multimodal data integration Exposure to federated learning, privacy preserving analytics, or distributed systems Knowledge of clinical data models
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, specifically methods that combine machine learning and optimization with physics-based simulation and/or physical constraints and translate these methods into impactful industrial applications. The position is
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programming models and high-performance computing techniques and machine learning models. Practical experience in the programming of high-performance computing of AI and/or scientific computing applications
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and deploy advanced deep learning and foundation models for surgical scene understanding segmentation, tracking, and operator assistance. You will write, test, and optimise Python and C++ code for real
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sciences, AI, machine learning or related fields. Strong background and track record in the development of geospatial foundation models from multi-modal Earth Observations is essential as well as strong
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Functions Developing and implementing machine learning and deep learning models to analyze forestry, physiological, and ecological datasets Modeling plant growth, carbon allocation, stress response (e.g