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(“overparameterized”) machine learning models, like probabilistic graphical models, deep neural networks, diffusion models, transformers, e.g. large language models, etc. SLT is based on the geometrical understanding
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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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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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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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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
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, and process improvements.? Project and Portfolio Management? Establish and lead a transparent portfolio governance model that balances strategic impact, risk, and organizational capacity.? Define how
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reliable data pipelines that power machine learning models, analytics platforms, and enterprise reporting. They will have responsibility for sourcing, cleaning, validating, and integrating data across
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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