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, integrative systems biology, and machine learning. Our research is focused on analyses of data generated within the biological, biomedical, biotechnological and life sciences areas. The section has extended
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, Computational Linguistics, Machine learning, Computer Engineering or related fields Preferred Qualifications: ● Strong experience implementing and training deep learning models in PyTorch, with attention
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programming such as Python, R, MATLAB, or other similar programs and experience in using simulation/optimisation models and advanced data handling techniques e.g. machine-learning techniques, statistics
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The AITHYRA-CeMM Joint International PhD Call in Molecular Medicine and Artificial Intelligence (m/f
-20 fully funded PhD positions here: https://apply.cemm.at/ Supported by the Medical University of Vienna, the Technical University of Vienna and University of Vienna, the AITHYRA and CeMM PhD programs
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. The University of Melbourne provides an outstanding environment in which to develop innovative research in mathematical and statistical data science, with opportunities for collaborations with machine learning and
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your work at international conferences. Supervise motivated PhD candidates and contribute to the research community. Shape the next generation of AI talent (50%) Teach engaging courses in AI, machine
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in any area of mathematics may be considered. Candidates must have a PhD in mathematics by employment start date. Candidates will teach undergraduate and graduate courses in mathematics, perform
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equipment in metabolomics, cell biology, time-lapse microscopy. You will work in a dynamic and highly interdisciplinary team including computer scientists, experimentalists and clinicians. You will be
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and scope of MS research. This PhD project employs advanced network analysis and Large Language Models to develop predictive models for MS progression. It involves constructing and analyzing a complex
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data in any area of finance, such as asset pricing, machine learning, ESG investing, how social networks affect finance, research replicability, regulatory data in finance, financial institutions, and