1,098 machine-learning-"https:"-"https:"-"https:"-"Fraunhofer-Gesellschaft" Fellowship positions
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the one of the relevant fields. Preferred skills: Experience in forest operations analysis, forest resource management, spatial data science, supply chain/logistics analytics, machine learning Analytical
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. Experience with programming, modelling, statistical analysis, or the use of data analytics, machine learning or artificial intelligence methods is desirable. Personal qualities Strong ability to follow through
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biology, mathematical and computational finance, numerical analysis, machine learning and data science or the Oxford Centre for Industrial and Applied Mathematics (OCIAM). The successful candidates will be
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or Machine Learning). The master thesis must be included in the application. Documented proficiency in English, please see requirements below. Requirements for proficiency in English This position requires
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of Computer Science and affiliated with the Information Systems and Human–Computer Interaction (ISCHI) research group. Your immediate leader will be the unit leader of the Information Systems and Human–Computer
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) Mammalian cell culture (experience with induced pluripotent stem cells and/or adult stem cells preferred) Machine learning and basic bioinformatics A proven solid research experience in the context of multi
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-omics datasets Developing and maintaining reproducible, well-documented analysis pipelines Applying and adapting machine learning and AI approaches to biological questions Collaborating closely with
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What You’ll Need: PhD in computer science, artificial intelligence, machine learning, computational biology, biomedical engineering, or a closely related quantitative field. Strong foundation in modern
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position is available to work in the area of Digital Twins for optical networks, making use of intelligent AI-driven control planes. The applicants should have a solid theoretical background on machine
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reactions, or transport mechanisms. • Experience in data-driven modeling or machine learning applied to membrane materials or separation performance analysis is a strong advantage. • Candidates with strong