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, Pharmacology, Statistics, Data Science, Artificial Intelligence
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mechanisms using computer simulations and the methods of non-equilibrium statistical physics. The Research The PhD student will work under the supervision of Dr. Philip Bittihn within the European Doctoral
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intrinsic noise. These skills will be gained in part through scientific research that applies techniques from statistical and condensed matter physics to understand how phenomena in biological systems – key
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Master’s degree (or equivalent) in a relevant discipline such as computer science, mathematics, physics, or data science. They should have strong analytical skills related to statistics, machine learning
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in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the
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methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team orientation excellent
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. Please indicate in your application which of the above listed projects is most intriguing for you. Your profile Eligible candidates have strong skills in computational molecular (bio)physics, statistical
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biological targets) on experimentally relevant temporal and spatial scales. Using statistical methods, links will be established between a detailed description of radiation damage events on the nanoscale
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project work plan and milestones Your profile Completed university studies (Master/Diploma) in the field of Chemical/Metallurgical/(Mineral) Process Engineering, Data Science, Statistics, Machine Learning
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production of bacteria via mass spectrometry Statistical analysis of the resulting data The successful candidate will have the opportunity to work towards a PhD Required qualifications: University degree (M.Sc