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) with excellent grades in computer science, materials science, physics, or a related discipline Practical experience in data science, including the application of machine learning (ML) methods or large
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physics, microbial ecology, plant nutrition, plant physiology, plant ecology, biochemistry, and/or bioinformatics Strong interest in using process-based mathematical modeling to simulate biogeochemical
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
DNA thermodynamic database, coarse-grained simulations of DNA motifs, and existing experimental data to establish an AI model that is able to guide the construction of desired secondary structures
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computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm
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activity (work, studies, etc.) in Germany for more than 12 months in the last 36 months Master’s degree in physics, electrical/electronic engineering, computer science, mathematics, or a related field
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that demand interdisciplinary solutions? Then the Program for Collaborative Doctoral Projects is the perfect opportunity for you. Many of today’s most pressing problems can only be tackled through
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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Berlin, and the Max Planck Institute in Hamburg. Our work combines physics, chemistry, and materials science – pushing the frontiers of quantum materials research. The overarching goal of the Collaborative
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semiconductor properties to the composition of lead-free double perovskites Your Profile: Master’s degree in theoretical or computational physics, chemistry, materials science, or a similar field Familiarity with
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academic area such as applied mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, Python or equivalent) and