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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
self-assemble from a number of interacting single-stranded DNA molecules. An accurate prediction of DNA structures still remains difficult, which significantly slows down the development of new desirable
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applying systems biology and constraint-based modelling approaches, we aim to capture host–microbiome interactions at a mechanistic level and predict metabolite fluxes relevant to brain health. The project
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machine learning approaches to quantitatively analyze experimental data and predict emergent multicellular behaviors under varying mechanical and chemical environments. For more information about our lab
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Leibniz-Institut für Präventionsforschung und Epidemiologie – BIPS GmbH | Bremen, Bremen | Germany | 26 days ago
prediction Analysis of primary and secondary data Preparation of reports and English-language publications Presentation of results at conferences The Leibniz Institute for Prevention Research and Epidemiology
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). These collaborations enable practically relevant and breakthrough results. This team goal requires a quantitative model describing and predicting sperm motility under various conditions. You will develop the digital
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Multidimensional Omics Data Analysis You will be responsible for Prediction of metabolic activity in complex microbial communities, leveraging
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techniques. These surrogates will be tuned for rapid, uncertainty‑aware predictions and integrated into decision‑support tools for deep geological repositories of nuclear waste—one of the most pressing
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developmental, stem cell and cell biology systems) to predict, observe, and manipulate epigenetic processes. https://www.helmholtz-muenchen.de/ife The Schneider group is recruiting a PhD student to work on the
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) to predict, observe, and manipulate epigenetic processes. The Schneider group is looking for a PhD candidate (f/m/x) to work on the interphase between epigenetics and cellular metabolism. The applicant should
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sensitivity analysis, impact of the individual process parameters on the target properties and develop predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy