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on knowledge of chemical production technology, (ii) dealing with the spatial distribution of the value chain when assessing the sustainability of pharmaceuticals, and (iii) dealing with technological
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Gutenberg University (JGU) Mainz, the Donders Institute for Brain, Cognition and Behaviour in Nijmegen, Fontys University of Applied Science in Eindhoven, SURF and IBM, combining expertise from experimental
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for this include automated reverse engineering with state machine inference to spot flaws in the program logic, the LangSec (Language-theoretic Security) approach to structurally improve input handling, and security
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(photonics), electrical engineering or a related field? And would you like to be involved in research and development for detecting gas-phase contaminations in different novel/demanding applications
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PhD Candidate: Neurocognitive Mechanisms of Alternative Thinking at the Donders Centre for Cognition
to research using a new neuroimaging technology to track neural activity during communicative and emotional control challenges? Then join the Donders Centre for Cognition as a PhD candidate! This project aims
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an enthusiastic young scientist who likes to work with and develop novel laser-based spectroscopy instruments? Do you hold a Master’s degree in physics (photonics), electrical engineering or a related
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PhD Candidate: Neurocognitive Mechanisms of Alternative Thinking at the Donders Centre for Cognition
you fascinated by the connection between adapting communication and managing emotions? And do you want to contribute to research using a new neuroimaging technology to track neural activity during
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focuses on integration of the developed technology into a sensor. For the success of the programme, a close collaboration between the two projects and with the other project partners is crucial. Besides the
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whether findings generalise across various contexts. Requirements Specific Requirements You have a Master's degree in social science, science and technology studies, philosophy of science, or a related
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(e.g. augmented hearing, assistive hearing technology) as well as neuroscientific applications (e.g. models of neural encoding). This project aims to leverage self-supervised learning approaches