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Geosciences, Environmental sciences, Civil or Environmental Engineering, Physics or Mathematics or a related discipline Experience in programming (e.g., Python, MATLAB, or similar), interest in machine learning
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The Department of Biostatistics at the University of Washington has an outstanding opportunity for a postdoctoral scholar. The postdoctoral scholar will develop statistical machine learning and artificial
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conduct research on the theoretical foundations of mathematical optimization, as well as its applications to emerging challenges in machine learning and engineering. You will write and submit research
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to the fundamentals of spatiotemporal data science and machine learning using scripting languages. Supervise BSc and MSc thesis students conducting research in Geo-information Science. You will work here The research
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computational biology/chemistry, machine-learning for biological or chemical data, and drug discovery/design. Mentorship is taken seriously and every effort will be made to ensure the candidate is able to achieve
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, safety, respect, integrity and teamwork. Desired skills: Prior research experience in federated learning, distributed learning, or privacy-preserving machine learning. Experience with large-scale model
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systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning
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of Helsinki. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed
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some of the following areas (not all are required): Large-scale data analysis and learning analytics methods Experimental or quasi-experimental design; validity and measurement Working with LLMs
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a cover letter, CV, and contact information for three references. Review of applications will continue until the position is filled. Applicants may learn more about professional development