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neurosurgical centre. In this role the successful candidate will develop deep learning algorithms & validate models on diverse clinical data which include magnetic resonance imaging (MRI) and computed tomography
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complex research projects involving multiple interdependent components. Experience in programming (python) and applying AI-assisted technologies to streamline research and analysis workflows is highly
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take responsibility for the planning, execution and analysis of high-quality research, ensuring the validity and reliability of data at all times and will maintain ongoing scientific discussion with
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should have a PhD (or close to completion) in Physics, Planetary Sciences or Earth Sciences. It will be an advantage to have experience in remote sensing, analysis of thermal data, thermal modelling
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good understanding of the relevant basic theory, skills in data analysis and numerical modelling, and a strong research track record. Please direct enquiries about the role to: Only applications received
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defending the cultural value of knowledge for its own sake. You will also possess computational expertise in data mining and / or analysis, ideally including language processing, and be able to work with an
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the research team around Univ.-Prof. Dr. Philipp Grohs. Our ideal candidate has a strong interest in Applied Mathematics, possesses solid and profound background knowledge in Numerical Analysis, Approximation
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, particularly those involved in the analysis of digital topographic data and in field-based earthquake geology. The post is funded until 31 March 2027, with a possibility for longer term extension contingent
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stakeholders. The successful applicant will be expected to lead and develop qualitative research activities, data analysis and project support. The applicant will have responsibility for leading research
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for the development of the autonomous quantum processing unit (AQPU) as follows: Carry out design, experiments, and/or data analysis on specific research topics that we consider most important for realizing the AQPU