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candidates will be required to fund the difference between the home fees and international fees. Overview Are you interested in developing Brain-Computer Interface technologies to control brain stimulation in
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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, computational biology and AI. We aim to appoint one postdoctoral scholar with strong computational skills and a second experimental postdoctoral scholar to work at the interface between the two labs to integrate
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Mar 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Design
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interface with cyber and physical aspects of power systems such as the software-defined networking (SDN) in the microgrid control. Supervised by Prof. Xin Zhang (cyber-physical power systems) , the PhD
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no application deadline. Please refer to https://www.imprs-stns.mpg.de/application for details. Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double
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neuroscience and (4) the development of computational models and methods for neuroscience. The goal is to implement advanced brain-on-chip models and CRISPR-based screens and methodologies to generate
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candidates in all areas of Biomedical Engineering are encouraged to apply, with strategic interest in: Bioelectronics Brain-Computer Interfaces Biomaterials and Biomanufacturing Organoids and Organ-on-a-Chip
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The School of Materials Science and Engineering (MSE) provides a vibrant and nurturing environment for staff and students to carry out inter-disciplinary research in key areas such as Computational
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, visit: https://sites.google.com/view/tommaso-giovannini The ideal PhD candidate has: a solid background in theoretical/computational condensed-matter physics or chemistry (MSc in Physics, Chemistry