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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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COMSOL, Ansys Fluent, or OpenFOAM Excellent knowledge of thermodynamics, fluid mechanics, and heat & mass transfer Strong programming skills in Python, C++, or similar languages Familiarity with machine
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knowledge of thermodynamics, fluid mechanics, and heat & mass transfer Strong programming skills in Python, C++, or similar languages Familiarity with machine learning methods for optimization is an advantage
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at the nanometer scale. We will use available 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
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methods, thermodynamics of solvation shells, constant-pH simulation methods, Markovian thermodynamics, as well as functional mechanisms of the ribosome, fatty acid synthase, CRISPR/Cas, or intrinsically