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partners at Princeton and Chicago Present findings at international conferences and co-author publications in high-impact journals Qualifications Master's degree in Physics/Physical Chemistry with excellent
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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, digitalisation, AI and smart technologies, policy impact analysis, and/or production efficiency and markets. leading to an internationally competitive PhD degree and internationally peer-reviewed publications
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and spectroscopy Construction and optimization of single-molecule microscopy setups Development of image- and signal-processing software for single-molecule microscopy and spectroscopy data Analysis
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into goal-directed behavior. We use state-of-the-art approaches including functional brain imaging, automated behavioral analysis, and computational neuroanatomy. We value a collaborative atmosphere, early
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
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based at DIGIT as well as the collection and analysis of requirements from existing partners. In addition, further partners are to be integrated into the network and new formats and pilot projects
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microscopy and automated image analysis Basic knowledge of toxicology (e.g. through DGPT training courses or relevant studies / professional experience) Experience in establishing test methods Conscientious
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plan by conducting experiments, sample and data analysis, and write up of results for scientific publication are part of the PhD process – a journey to become an independent researcher! Throughout
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a four-year research project. Execution of the research plan through conducting of experiments, sample and data analysis and write-up of results for scientific publication are part of the PhD process