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). For more information: https://www.cordis.europa.eu/project/id/101225380 Research focus The PhD candidate will work on one or more of the following interconnected areas: AI‑ and machine‑learning‑based
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data at an internationally competitive level. Experience of biostatistics or machine learning approaches Proficiency in a scripting language like R or Python, as well as ability to work efficiently in a
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of experience in training, evaluating, and deploying machine learning models, including deep neural networks and relevant frameworks - Documented several years of experience in systems development with Python and
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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Project description Third-cycle subject: Biotechnology The project aims to develop probabilistic deep learning models
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candidate will collaborate with various research groups, expand professional network and acquire advanced biochemical and computational skills. This project builds upon our team’s established expertise
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areas (demonstrated through peer-reviewed articles or pre-prints): Applied Machine Learning (ML) for industrial settings like part-autonomous robots, and building simulation or test environments
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the design of antibody modalities Documented experience from cancer-related research Documented research experience in AI/machine learning/deep learning Documented experience in the development of therapies
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manipulation tasks. We are seeking candidates with a strong background in robotics and machine learning, and demonstrated experience in two or more of the following areas: deep learning, reinforcement learning
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sciences domain. The person we need We are looking for someone with broad subject knowledge in life sciences, with a focus on machine learning, as well as a willingness and proven ability to work in
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: developing and applying image analysis and sensor technologies (e.g. RGB/NIR) for textile production, as well as using machine learning for process optimisation and performance prediction from fibre