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& Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable implementations. By establishing a new class of multi-frame
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objective of the project is to develop knowledge, models, and algorithms for physics‑informed autonomous control of heavy machinery in uneven and deformable terrain. Specific project tasks include fundamental
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through theory and simulation and/or experimental design and testing; developing new image reconstruction algorithms for providing more information with less radiation; and applying our techniques
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vulnerability with respect to a DES property of interest; and (iii) testbed demonstration of any developed modeling techniques and algorithms. Responsibilities and Duties Interdisciplinary research on CPS
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Overall, Purpose of the Job We are looking for one Research Associate to work on the development, implementation and testing of predictive control algorithms for the optimal coordination
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of the analysis of in-situ experimental data in the field of non-destructive testing (digital image correlation, thermography and acoustic emission) development of algorithm-supported evaluation methods in
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-edge optical microscopy systems for biomedical applications. This project involves the development of compact, label-free quantitative tomography systems and inverse scattering algorithms to push the
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. Developing and applying state‑of‑the‑art artificial intelligence and machine learning (AI/ML) algorithms to discover robust prognostic and predictive biomarkers, and design clinically actionable treatment
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processing using Artificial Intelligence (AI) algorithms, integrated as an energy-efficient Point-of-Care computing tool. The system will be developed following a co-creation methodology involving key
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team focuses on the formal analysis of security protocols and studies numerous protocols, including electronic voting. The team has developed several algorithms to prove protocol security and regularly