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model we deploy and support the ecosystem with training, advisory, and AI infrastructure. CeADAR is seeking a data scientist with solid experience in machine and deep learning research and development
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of user support services, including network support, training, and computer desktop support. This role involves end-user support and training, focusing on endpoint technologies (desktops, laptops
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at finale.seas.harvard.edu and our group’s webpage https://dtak.github.io/ We work on probabilistic models, reinforcement learning, and interpretability + human factors. Basic Qualifications Candidates are required to have
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adaptation of pre-trained microscopy vision models and cross-modality representation learning/ alignment. You will build robust pipelines that adapt foundation models to specialized microscopy tasks and
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++ or similar) and an interest in quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not
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statistics, scientific programming, and/or modelling. We especially welcome candidates interested in applying AI and machine learning to analyse heritage datasets. What we offer: • A stimulating
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(AWS, Azure, or Google Cloud) Experience with Machine Vision Experience with fine-tuning foundation models Experience with writing and maintaining APIs Modes of Work This position is classified as having
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collaboratively within an interdisciplinary research environment. Desirable experience with advanced AI or machine-learning methods beyond standard predictive modelling prior exposure to qualitative or mixed
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for farm-farm interaction Development of coupled LES and aero-elastic models using the actuator line method Analysis and design of wind farm control through LES and machine learning Scientific publication
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tasks that require coordinated base-arm-hand behaviors in dynamic environments. We seek candidates with a strong background in robotics and machine learning, and demonstrated experience in at least two of