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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome
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well as innovative and inquiry-based teaching and learning. The Faculty consists of six departments as well as a Faculty administration. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/296312/phd
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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lab’s website https://sites.duke.edu/corinnelinardiclab/ . Be You Work Performed · Perform literature reviews to guide research · Design and execution of standard in vitro assays ongoing in the lab
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projects of the MQS group. Our recent research has focused on the theory and applications of variational quantum algorithms and quantum machine learning. We also have activity in quantum optics, so
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the rank of Research Assistant Professor in computational mathematics, machine learning, scientific computing, statistics, and related areas. The appointee is expected to conduct high-impact research
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modelling predictions. Experience or a strong interest in scientific programming and machine-learning-assisted data analysis for materials modelling is an advantage. PhD Position 2 – Coarse-Grained and
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command of written and spoken English • Experience with qualitative research methods is an asset • Good knowledge of machine learning /data mining in science • Good programming skills in at least one
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at the rank of Research Assistant Professor in applied probability, data science, machine learning, and spatial statistics. Candidates with a strong background in the development of novel models and original
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industrial component given the close collaboration with the quantum computing start-up, Quantum Motion, particularly with Dr. Ciriano-Tejel, machine learning group. Key responsibilities Conduct research