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beginning in the 2027-28 academic year. Qualifications We invite applications from those who hold a PhD (or equivalent) in the relevant field(s) or expect to complete the requirements for a PhD in accounting
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seizures/epilepsy, including stereotactic injections and implantation of multichannel recording and stimulation electrodes. Acquire, curate, and analyze multichannel iEEG/electrophysiology recordings from
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researcher who enjoys developing methods for complex biological data and working closely with experimental scientists. You meet the following criteria: a PhD, or a PhD close to completion, in machine learning
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checks with advanced machine learning architectures, specifically Long Short-Term Memory (LSTM) networks and Variational Autoencoders (VAEs). The researcher will use historical QC archives dating back
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Join the Responsible Machine Learning (ML) Group at the Faculty of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research
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analyse electrochemical free-energy landscapes and connect elementary-step energetics to catalytic performance apply machine-learning interatomic potentials and microkinetic models where appropriate
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paradigms that support collaborative processes rather than isolated individual use. Combining perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported
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of reactive force field molecular simulations, supervised machine learning techniques and understanding of mass spectrometry techniques. The post is available for 3 years from 1 September 2026. If you are still
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to teaching, clinical evaluation, mentorship, scholarship, service, and academic-practice partnerships that support the Family Nurse Practitioner program and broader College of Nursing priorities. Teach
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Constructor Technology, invites applications for a PhD position in machine learning for software engineering and formal methods, on the Constructor Fabric project. Constructor Fabric turns a company's informal