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administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate 51 Faculty of Physics Startdate: 01.04.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr
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. General computer skills and ability to quickly learn and master computer programs, databases, and scientific applications. Strong analytical skills and excellent judgment. Ability to maintain detailed
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3GPP compliant 5G/6G NR NTN OFDM waveforms Develop and analyse signal processing and/or machine learning algorithms for joint channel, delay, Doppler and carrier phase estimation, remote object ranging
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the application of these methods to problems in the physics of oxides, semiconductors, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists
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, and computational models. This PhD position is centered on addressing these challenges through innovative computational methods, combining optical system design, signal processing, machine learning, and
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). The ideal candidate brings a strong machine learning foundation, curiosity about sound and music computing, and enthusiasm for collaborating with PhD students and postdocs. You will help combine individual
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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for a dedicated PhD student to join our team. Find more information about the Strategic Management area and its members here: http://strategy.univie.ac.at What you will be doing: In
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between the brain signals of different subjects. The aim of this project is developing new adaptive and machine learning algorithms to successfully decode brain signals across subjects. The prospective
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to machine learning. This PhD provides a unique opportunity to shape emerging concepts in Artificial Intelligence Informed Mechanics (AIIM), combining fundamental research with methodological innovation. You