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Your profile PhD applicants must possess a Master's degree in mathematics, theoretical physics, or computer science. Candidates should have an exceptional academic record and a robust mathematical foundation. Candidates are also expected to have strong coding and implementation skills, with the...
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applications, including solving mathematical reasoning problems and tackling the Abstraction and Reasoning Corpus (ARC) challenge among others. The ideal candidate has a strong background in machine learning and
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, biology, or a closely related discipline Desirable experience: optics and photonics, AI/machine learning, biology, or biomedical sciences Excellent English, analytical, and problem-solving skills UK
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Disse), the Chair of Geoinformatics (Prof. Thomas H. Kolbe), and the Chair of Algorithmic Machine Learning & Explainable AI (Prof. Stefan Bauer). The project aims to develop an integrated urban flood
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machine learning approaches. These are similar to earlier work on charge and excitation energy transfer (see https://constructor.university/comp_phys). The project for the PhD fellowship is slightly more
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patient samples. The Sheffield arm of the project will develop statistical and machine learning models to identify and validate predictive biomarkers of resistance evolution in Pseudomonas aeruginosa lung
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? This PhD project offers a unique opportunity to apply machine learning to solve a critical engineering challenge within the railway industry. The Challenge: Rail grinding is a crucial maintenance activity
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-harvesting complexes. The research will use a combination of quantum and molecular dynamics simulations, electronic structure calculations, and machine learning approaches. These are similar to earlier work
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information For further information, please contact Prof. Ants Kallaste ants.kallaste@taltech.ee and Prof. Anton Rassõlkin an- ton.rassolkin@taltech.ee or visit https://taltech.ee/en/electrical-machine-group
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, epidemiologists, clinicians and lab researchers, with expertise in the field of prediction modeling, longitudinal data analysis, statistics, data science, machine learning, AI, organoid models and cystic fibrosis