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Field
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(Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP
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with vessel protected volume estimates to identify safety-buffer overlaps, developing multi-agent path-planning, and machine-learning methods for corridor allocation, airspace capacity optimisation, and
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an industry partner. Experience with research software, data pipelines, and simulations, machine learning, high-performance computing, CANFAR, or advanced data systems. Evidence of mentoring or supervising
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, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C++. Demonstrable experience with machine learning frameworks (e.g., PyTorch, TensorFlow
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, procurement, or grant administration will be an added advantage. Experience in areas such as Machine Learning, Deep Learning, Computer Vision, Large Language Models, Data Analytics, or Intelligent Systems will
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Able to adapt to change, Able to assemble, analyze and present data, Able to learn and retain information, Able to multitask, Able to plan, organize, and implement projects in a timely manner, Able to
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, machine learning, and multi-omics technologies to drive discoveries that have the potential to transform cancer diagnosis, treatment, and patient outcomes. This is an exceptional opportunity to create
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machine-learning models to investigate how brain, environment and social factors influence cognition, ageing and neurodegenerative disease. The role will contribute primarily to WP6 and related analytical
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standards and data protection regulations. This includes managing sensitive data correctly and guaranteeing that machine learning applications are developed with ethical considerations in mind. Participate in
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, along with Christmas closure Ride to work and EV car scheme available For more information, please see University of Manchester Benefits . You can also find information on our Flexible and Hybrid working