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explored using scientific machine leaning. Machine learning, programming experience and a curious mind-set You are fascinated by how computers can learn from data and you have a strong interest in the
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. The position is an Alliance PhD partially funded by DTU and partially funded by Villum Fonden under the Villum Young Investigator program. The PhD project will investigate the molecular basis of enzyme-substrate
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program, which includes tailored training, workshops, retreats, and conference travel. You will have access to cutting-edge laboratories and theoretical methods, individual supervision, and a wide range of
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/GPUs. These devices provide massive spatial parallelism and are well-suited for dataflow programming paradigms. However, optimizing and porting code efficiently to these architectures remains a key
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to the faculty's Doctoral Programme Proficiency in spoken and written English. PLEASE NOTE: For detailed information about what the application must contain, see paragraph “About the application”. The appointment is
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science or related discipline Experience and skills Experience in developing MLIPs, including good programming skills in Python and C, demonstrated via contributions to code repositories Experience with
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Max Planck Institute for Extraterrestrial Physics, Garching | Garching an der Alz, Bayern | Germany | 24 days ago
with at least a grade of 'good'. Experience in programming in C, C++, Python, or IDL (or any equivalent) is desirable, as well as experience in the analysis of imaging radio data. The full-time PhD
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track. Ideal candidates are late-stage Assistant Professors or Associate Professors who have demonstrated early success in establishing independent research programs, including securing independent grant
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to develop long term, quantitative strategic plans that emphasize sustainable agribusiness enhancement. This PhD position is carried out in collaboration with the Doctoral Program in Agricultural and Forestry
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, with a particular emphasis on column generation approaches. Column generation is a powerful decomposition method for solving large-scale linear and mixed-integer programming problems. Rather than