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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
quality. Secondly, different machine learning strategies based on traditional supervised learning techniques (e. g. random forest (RF), artificial neural network (ANN)) will be applied using the parameters
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work will focus on identifying the mathematical knowledge and properties to guide hardware optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g
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. Your work will focus on identifying the mathematical knowledge and properties to guide hardware optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g
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embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work
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, prior interactions, rank differences, and kin relationships). We will explore the implied cognitive complexity of great ape communication to identify evolutionary trends and simulate dynamics that might
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qualifications You have graduated at Master’s level in computer science or completed courses with a minimum of 240 credits, at least 60 of which must be advanced courses in computer science, mathematics, AI
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27 Oct 2025 Job Information Organisation/Company Helmholtz Zentrum Hereon Research Field Chemistry » Biochemistry Engineering Physics Mathematics Researcher Profile First Stage Researcher (R1
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). Acceptable first degree: Natural sciences, Environmental sciences, Physics, Chemistry, Mathematics or a similar numerical subject. Mode of Study: Full-time Start Date: 1 October 2026 Funding Information ARIES
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strong numerate background. Prior experience of mathematical or statistical programming is highly desirable. Informal enquiries concerning the project are welcomed by the primary supervisor. Entry
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solve complex problems from theory to decision making, combining several disciplines (e.g. economics and applied sciences). A candidate with strong statistical/mathematical knowledge and experience