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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | about 8 hours ago
analysis platforms integrating AI and machine learning pipelines Coding skills in Python or R for data processing and visualization is an asset Fluency in English (spoken and written) Strong scientific
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experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
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Sciences, who develop, manage, and refine machine learning techniques for identifying copyists; Participation in the dissemination of research results through presentations and publications; Data management
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and the terms of the research grant when extending an offer. Completion of PhD in Data Science, Computer Science, Mathematics, or other discipline aligned with CDS faculty research by the start date
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 21 hours ago
/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales
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analyzing urban data (traffic, energy consumption, environment). Strong skills in integrating IoT devices into complex digital systems. Advanced expertise in machine learning and artificial intelligence
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or equivalent and a PhD (or close to completion) in computer science, math or comparable, or an applied/life science (e. g. engineering, biology, medicine) with a focus on data analysis and/or machine learning
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together with relevant experience. You will have a strong technical background in machine learning, especially RL and LLMs. An ability to work independently and as part of a collaborative research team is
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, and you will join the research group led by Prof. Christa Cuchiero to work at the intersection of Mathematical Finance, Stochastic Analysis and Machine Learning. The research areas cover a wide range of
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) prediction models to ensure the safety, efficiency, and longevity of lithium iron phosphate (LFP) batteries. Key Responsibilities: Develop and implement machine learning algorithms for SOC and SOH estimation