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Field
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verbal, written communication skills In-depth knowledge of deep learning, specifically VLM models, computer vision techniques (e.g., open vocabulary object detection, model distillation, VQA, test-time
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for structural biology. This project sits at the intersection of X-ray scattering and deep learning, aimed at integrating experimental data to predict protein ensemble structures. As an Empire AI-funded fellow
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, and multimodal deep learning approaches that enable privacy-preserving learning across distributed healthcare data sources Support health outcomes with research in transformative applications in
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where our people are empowered to thrive through supportive leadership, shared responsibility, and a deep commitment to genuine care and respect for our community. Find out more about our vision for a
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related to staff position within a Research Infrastructure? No Offer Description At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and transferable
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metabolism in ageing models. The use of AI and Deep Learning for data analysis and the establishment of in vitro ageing experimental systems and factor isolation using CRISPR Screening are also planned
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experiences are valued, and where our people are empowered to thrive through supportive leadership, shared responsibility, and a deep commitment to genuine care and respect for our community. Find out more
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computer vision and vision-language models Experience with ML evaluation metrics and benchmarking Proficiency in Python and deep learning frameworks (e.g., PyTorch) Interest in applied, industry
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/ESA_selects_Harmony_as_tenth_Earth_Explorer_mission ) The candidate will develop and apply cutting-edge remote sensing or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via
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intelligence. Strong knowledge and research outputs in AI, particularly in the field of deep learning, knowledge representation and reasoning, or neuro-symbolic AI. Proven commitment to proactively keeping up