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We invite applications for a full-time Postdoctoral Research Associate to join the new Data-Driven Algorithms for Data Acquisition (DataAcq) project. This is a timely project developing new
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 18 days ago
40 research groups and some 1,000 employees from over 50 nations, it is the largest institute of the Max Planck Society. The Department of Theoretical and Computational Biophysics headed by (Prof. Dr
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models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations and/or experimental
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of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or experimental means. The PDA is expected to actively disseminate results through publications in
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, Dental Materials, Dental Technology or a related discipline, with research experience in Non-linear Finite Element Analysis, CAD for dental prostheses, AI algorithm development using python / PyTorch, and
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focus on the fluid-structure interaction algorithm developments. The project leadership team consists of Dr Mokarram Hossain and Prof. Djordje Peric at Swansea University and Dr Chennakesava Kadapa and
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Dutch and English. Affinity or experience with innovation projects involving partners from practice. Willingness or experience in programming heuristics and algorithms. Motivation to produce academically
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data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms to understand
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data
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across domains. The research unit Intelligent Systems (IS) in Computer Science is focused on the development of Data Science, Pattern Recognition and Machine Learning algorithms for interdisciplinary data