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discipline Strong experience in integrating several of the following components: Deep learning and LLMs for molecular biology Vision foundation models for pathological image analysis Multi-omics datasets (e.g
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quantitative and machine learning approaches ● Developing predictive models linking nuclear features to future cell fate ● Interacting with collaborators in imaging, computational biology, and developmental
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candidate will have recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically
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focused on exploration and development of AI models of auditory perception, towards a broader goal of understanding how the brain predicts and learns from human communication sounds such as speech and music
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highly multidisciplinary environment, collaborating closely with radiologists, software engineers, and data scientists to advance clinically relevant AI methods. Your research is expected to lead to high
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postdoctoral research positions within a multidisciplinary project supported by Schmidt Sciences under the VIEW programme. The project, in collaboration with Imperial College London, EPFL, and multiple partners
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collaboration with research partners at DEVCOM Army Research Laboratory (ARL) and industry. The position focuses on additive manufacturing processes, including solid-state and fusion-based methods such as
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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. Weinstein (DTU Chemistry) to develop novel molecular ML methods and use them to control, steer, and learn from large scale wetlab experiments. You will deploy these methods in collaboration with Prof. Katrine
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professional development, instructional moves enacted by laboratory teaching assistants, laboratory curricular design principles for inviting conceptual understanding and collaborative inquiry, and institutional