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evolution. Previous experience in mathematical modelling of biological processes is valuable. Workplace Workplace We offer ETH (Swiss Federal Institute of Technology) and Eawag (Swiss Federal Institute
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modeling tools with tailored laboratory experiments and theoretical models, we create a holistic perspective on mechanical failure, bridging the gap between material behavior at the small scale and
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. Professorship in Pathogen Evolution (ETH Zurich and Eawag) is seeking a highly motivated PhD Candidate to study drug resistance evolution in various pathogens through population genetic modelling and
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computer science and applied mathematics to develop state-of-the art generative machine learning models to design improved catalysts for these reactions. Profile We are looking for a committed and motivated
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experiments, and enhanced geothermal systems worldwide. Job description The PhD student will focus on constructing and training advanced machine learning models tailored to characterize induced earthquakes
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included in the modelling of the experiment. Such an approach will require: Extending and improving an existing framework for optimizing pulse sequences based on effective Hamiltonian calculations Numerical
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digital platforms. Job description Selected candidates will engage in groundbreaking research, contributing to publications in top-tier journals. Responsibilities include handling generative chatbot models
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science, statistics, applied mathematics, or related fields Proficiency in developing and deploying machine learning models (e.g., using Python, R) Experience in data wrangling and feature engineering
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for Project II Masters or equivalent degree in mathematics, computer sciences, physics, chemistry or related disciplines Very good programming skills Experience and knowledge in the fields of DFT modelling