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, 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 the project, there will be multiple
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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
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, investigate error mitigation techniques Cooperate and actively work with international collaborators Your Profile: Master’s degree in physics, mathematics, or computer science Strong interest in both developing
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. This exciting project will focus on designing, constructing, and testing synthetic cells with multiple sub-compartments. Just like their living counterparts (i.e. eukaryotic cells), synthetic cells with different
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addition to debits, credits can be obtained. The research performed under this internship by an Electrical/Power Engineering or Computer Science PhD student will relate to this reform, specifically investigation
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”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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and rural health staff informatics, coordinate the writing of ethical applications and reports, and contribute to writing publications and external grants. To be successful you will need: A PhD in
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relevant to multiple applications, including small aircraft, drones, turbines, and other systems reliant on efficient fluid flow around foils. The project offers a unique opportunity to gain experience in
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institutions around the world Continuous scientific mentoring by your scientific advisor as well as feedback and wide-ranging expertise from the whole group in multiple facets of quantum technology and
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Science or German Diplom, preferably in biology, chemistry/biochemistry, psychology, medicine, physics, engineering, or informatics neuroscientific knowledge and interest in an interdisciplinary research