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Field
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We are seeking a highly motivated PhD student to perform fundamental research and to conceive truly sparse solutions (on both, CPU and GPU) for dynamic sparse training, aiming to cut the training costs and energy requirements of state-of-the-art deep learning models significantly, while...
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carries a clear expectation to develop an independent, externally funded research program, including preparation and submission of NIH R01-level grant applications, alongside manuscript authorship and
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Research Assistant to investigate digital reading comprehension through large-scale data analysis. This role, funded by the John Fell Fund, sits at the fascinating intersection of computational
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available to help identify options that may be suitable for your situation. Persons with disabilities who need assistance or accommodations with the application or interview process may contact University
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stage of the recruitment process for any candidate with a disability. We are open to considering applications from candidates wishing to work flexibly.
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of SOPs and process documentation. Coordinate efforts with Duke’s GMP Cell therapy Facility. Contribute to preclinical IND-enabling studies. Manuscript preparation. Data analysis Maintain accurate
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personalised medicine. The Department of Biomedicine provides research-based teaching of the highest quality and is responsible for a large part of the medical degree programme. Academic staff contribute
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program. Requirements Very good master's degree in computer science, data science, mathematics or a related discipline; relevant research experience (e.g., master's thesis) in the field of NLP/ML/text
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motivated and ambitious PhD candidate skilled in genetic epidemiology, biostatistics, mathematics computational biology or related discipline to contribute to the “Hereditary & Early onset breast cancer
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report on your progress regularly. You will participate in the doctoral study programme at the Antwerp Doctoral School to support your PhD pathway. You will present the findings of your PhD research