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Job Description We invite applications for a fully funded 3-year PhD position in the Embedded Systems Engineering (ESE) research section at DTU Compute in collaboration with the Technical
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
relevant field such as engineering, computer science, or applied mathematics. Experience or interest in AI, machine learning, or digital systems is beneficial. We welcome candidates from diverse backgrounds
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level (or international equivalent) in a science, mathematics or engineering discipline. Applicants without a master's qualification may be considered on an exceptional basis, provided they hold a first
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2025/07/14) Position Description: Apply Today is the last day you can apply for this position; no new applications will be accepted after 2025/07/14 11:59PM US Eastern Time. Position Description
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Summer 2026 or postdocs in quantitative fields such as Mathematics, Physics, Statistics, Electrical Engineering, Computer Science, Operations Research, or Economics Analytical problem-solvers with
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Application deadline: All year round Research theme: Applied Mathematics, Mechanical and Aerospace Engineering, Fluid Dynamics How to apply:uom.link/pgr-apply-2425 How many positions: 1 This 3.5
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, ecology, engineering, environmental science, information technology, mathematics, physics, or similar; or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses in
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should possess an M.Sc./M.Eng. degree in one of the following fields: Electrical and Electronics Engineering, Telecommunications Engineering or Computer Science/Engineering. Experience: The candidate
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University. Requirements A master’s degree in (applied) mathematics (or related), with a strong background in computational methods, preferably also using computational frameworks for machine learning in
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full-time career. What we're looking for PhDs (in penultimate or final year) in quantitative fields such as Mathematics, Physics, Statistics, Electrical Engineering, Computer Science, Operations Research