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variability in risk factor susceptibility, treatment response, disease pathogenesis, and clinical diagnosis (biostatistics, machine/deep learning), ii) Investigating causal processes and disease mechanisms
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Uppsala University, Department of Information Technology Are you interested in developing new image analysis and machine learning methods for precision medicine and clinical decision support? Would
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. Rocío Mercado Oropeza, applies machine learning to molecular engineering problems in life sciences and drug discovery, and is based in the Division for Data Science and AI within the CSE Department
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Wiberg is “Innovative statistical and machine learning methods for comparing performance and outcome in register data studies”, with overall aim to develop, evaluate, and implement innovative statistical
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well as the clinical activities at the Karolinska University Hospital, unique access to international expertise in machine learning, state-of-the-art imaging, diverse patient cohorts, and relevant computational
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or more of the following programming languages/environments: Unity/Unreal, C/C++, C#, Python Basic understanding of the artificial intelligence and machine learning fields. Place of employment: Karlskrona
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machine learning and computer vision techniques to enhance data analysis, pattern recognition, modeling, and prediction. The role requires a solid understanding of fluid dynamics and heat transfer, as
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of small cryptic plasmids in the development and spread of antibiotic resistance, and ii) Use machine learning tools to examine the complex interplay between bacterial hosts, various plasmids and resistance
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and verbal communication skills in English Experience in some of the following areas is meritorious: group theory, statistics, neural networks, machine learning and programming. Evidence of problem
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Chalmers' new research initiative Ocean is seeking a highly motivated PhD student in environmental analytical chemistry and machine learning. In this role, you will work with high-frequency