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at the top venues of machine learning research. Responsibilities and qualifications You should have prior experience with machine learning from both a theoretical and practical perspective. Experience in one
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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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large-scale speech and wearable data from participants in the GLAD Study cohort ( https://gladstudy.org.uk/ ). Using large language models (LLMs) and acoustic analytics, they will uncover patterns in
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sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT
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) ELEGANCE (machinE LEarning for inteGrated multi-parAmetric eNzyme and bioproCess dEsign), and it will focus on: Expression, characterization and application of enzymes from University of Turin and other
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning