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Conversion and Systems at the Aalto University School of Engineering invites applications for Doctoral Researcher in Sustainable Renewable Energy Engineering, Modeling and Optimization Department of Energy and
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from estimation and optimization theory to hardware design. The specific topic of the project falls in the intersection of statistical signal processing and applied mathematics and is in particular
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stability theory, modeling & identification, optimal control, certifiably safe & robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven
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skills and experience in written, spoken, and collaborative work in English. What we offer: A career path optimized for transition to industry. You will be affiliated with the dynamic Aalto Scientific
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in real-time experimental settings and optimize them for privacy-preserving healthcare monitoring. You will collaborate with healthcare professionals to validate solutions in use cases such as
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chemical activation method, and develop environmentally friendly electrolytes. Work will focus on: Preparation, characterization, and optimization of porous carbon electrode ink for supercapacitor
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, simulation environments and optimal control are appreciated. English language requirements: Proficiency in written/spoken English is mandatory. In certain cases, we may ask for a language certificate. We offer
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opportunity to engage in innovative research at the intersection of optimal control, machine learning and robotics. Job Description As ALCAN Research Group, we work on the safety and reliability of complex
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.0c02887 ). We are looking for a motivated student with keen interest towards experimental research and applications of trace gas analysis. An optimal candidate should have prior experience with optical
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leverage the theory of estimating functions to create optimal inference algorithms for the proposed loss functions based on its underlying Riemannian geometry, as well as for those previously introduced in