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in a university or college setting. Working knowledge of the content areas of probability, statistical methods, generalized linear models, statistical computing, and machine learning. Preferred
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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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the use of machine learning and AI approaches • Integration of proteomics with genetic data via MR, coloc and FUSION to identify causal and druggable targets Requirements • The successful applicant will
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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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or bachelor’s degrees through a combination of in-person, online or blended learning. All of our system institutions place strong emphasis on service — helping to build healthier, more educated communities in
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highly collaborative research team to accelerate and extend ongoing research efforts (including DL-based joint species distribution modeling and causal machine learning) and lead methods development
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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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Language Models (MLLMs) and their agentic implementations. Develop and benchmark novel adversarial attacks and defense strategies, focusing on the intersection of computer vision, natural language processing
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Engineering, or related fields. They must have proven experience in the development and programming of Information Systems; prior experience in applications based on Data Analytics/Machine Learning and data
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Hands-on lab experience and/or interest Knowledge on Machine Learning, or other AI techniques Personal skills: Team Worker Initiative in Research and Innovation Flexibility Results-oriented Analytical and