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robustness, fairness, and accessibility. You will design and run reproducible experiments, measure relevant resource metrics, implement prototypes in Python, and communicate results through publications and
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of machine learning such as robustness, fairness, and accessibility. You will design and run reproducible experiments, measure relevant resource metrics, implement prototypes in Python, and communicate results
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, administrative and technical support functions, along with good employment conditions. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/ . Project
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and technical support functions, along with good employment conditions. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/ . Project
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equations. Your main research assignments will be to develop new models and methods for generative sampling and Bayesian inference. You will be jointly supervised by Assistant Prof. Zheng Zhao (https
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solutions across the natural sciences. Your workplace You will be employed at the Department of Mathematics in the Division of Applied Mathematics, https://liu.se/en/organisation/liu/mai/tima . The research
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in written and oral English. Programming skills with Python. Consideration will also be given to good collaborative skills, drive and independence, and how the applicant’s experience and skills
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skills in English Programming skills with either Matlab or Python *for students with an education earned outside of Sweden, a 4-year Bachelor’s degree is accepted. The following experience will strengthen
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programmer in R and/or Python, and used to working with large datasets and reproducible analysis workflows. Has a demonstrated ability to initiate and drive own research ideas, preferably with experience from
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on developing biochar as a sustainable feedstock for hard carbon anodes in sodium-ion batteries. In collaboration with Besca AB (https://www.bescacarbon.com/ ), this project explores microwave plasma technology