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data. Building on these results and codebases, the successful candidate will work on a bioinformatics and machine learning research project on the inference of alternative splice forms using deep
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8 Dec 2025 Job Information Organisation/Company University of the Aegean(UoA) Department Research Unit Research Field Engineering » Electrical engineering Engineering » Computer engineering Physics
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PhD Research Fellow in ML-assisted reservoir characterization/modelling for CO2 storage (ref 290702)
-build ups in potential multi-site storage licenses. The research will help to suggest best practices for machine learning integration in de-risking CO2 storage sites. We seek a candidate with a strong
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challenges to global public health. Learn more about MET and their research here: https://www.hsph.harvard.edu/molecular-metabolism/. The lab of Dr. Nora Kory studies compartmentalization of metabolism and
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FieldMathematicsYears of Research Experience1 - 4 Additional Information Eligibility criteria - Thesis in natural language processing with machine learning, - mastery of NLP and machine learning methods and tools
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to positive change in society You can expect numerous benefits , such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ , childcare and attractive pension benefits
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, statistics, or mathematics OR a strong background in gene engineering and functional interrogation of hematopoietic stem and progenitor cells. Strong knowledge in bioinformatics, machine learning, statistics
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and methods for advancing the research effort Design and carry out computer experiments on deep learning and related robotic simulations Collaborate with other engineers to create prototypes of embodied
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to effectively teach genetics, biochemistry, and molecular biology to undergraduates in the lab setting. The research projects cover a large span of life science topics and technical approaches, including genetics
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research in Physics-Informed Machine Learning (PIML) for metal additive manufacturing process. This role will focus on developing novel machine learning frameworks that seamlessly integrate physical