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of the future, striving to improve healthcare and society as a whole. Where to apply Website https://www.academictransfer.com/en/jobs/356668/phd-in-machine-learning-for-dru… Requirements Specific Requirements
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cardiometabolic disease. This two-year position (with the wish and possibility of extension for another four years) is ideal for a scientist with deep technical expertise and passion of alleviating disease burden
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track record in wireless communication systems, machine learning, or related fields. Ability to work independently and co-supervise PhD students. Excellent command of the English language, both written
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, computer science, AI/ML, medicine, statistical genetics, psychology, molecular genetics, or a related field. Demonstrated expertise in machine learning, deep learning, or advanced statistical analysis applied
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Incorporating reinforcement learning strategies to guide model optimization, with a focus on minimizing immune responses and improving therapeutic viability Your Profile: Completed Master/PhD Degree in the field
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modulators of TDP-43 by conditional deep learning In ALS, TDP-43 is mainly in the cytoplasm with a loss of nuclear function and formation of toxic stress granules. Small molecules have been designed to avoid
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position for one Research Grant (“Bolsa de Investigação“) is open at Instituto de Telecomunicações, in the scope of the Project DECOLLAGE project – DEep COgnition Learning for LAnguage Generation, supported
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at the forefront of medical science, and educators to advance learning. We are proud to be part of progress, working together with the communities we serve to share knowledge and bring greater understanding
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(Wissenschaftszeitvertragsgesetz - WissZeitVG). The position offers the chance to obtain further academic qualification (usually PhD). The project: We are seeking motivated researchers to join our international team
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, GNSS positioning is highly susceptible to errors from atmospheric distortions, multipath effects, and receiver noise. Recent advances in deep learning have shown that data-driven pseudorange correction