307 machine-learning "https:" "https:" "https:" "https:" "https:" Fellowship research jobs
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the areas of stochastic analysis and computational methods towards machine learning with focus on risk-sensitive decision making and control. Techniques may include forward, backward stochastic differential
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dissertated before the start-up date of the position. A research profile with relevant experience in biological sequence analysis, with complementary skills in machine learning or other relevant algorithms. A
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Internal Number: 528197 Pay Grade/Pay Range: Minimum: $53,500 - Midpoint: $66,900 (Salaried E8) Department/Organization: 214251 - Electrical and Computer Eng Normal Work Schedule: Monday - Friday 8:00am to 5
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environments will provide the successful candidate with opportunities to learn from a large network of talented professionals. Prof. Mariam Jamal-Hanjani is Principal Investigator of the TRACERx study at UCL
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fluid dynamics. The successful candidate will be expected to work on all or a subset of the above topics, be proficient in working with large data-sets (observational or numerical), machine learning, and
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per year. The successful candidate will be able to teach Introduction to Comparative Politics, in addition to an intermediate-level European politics course and a thematic course in a more specific area
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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Qualifications ? Ph.D. in Physics, Materials Science, or a related field with a concentration in electron microscopy methods ? Experience in the collection and processing of TEM/STEM data ? Computer programming
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modelling, machine learning, growth mixture modelling). Excellent skills in statistics and advanced quantitative data analysis, including strong skills in command driven programming languages (e.g., STATA, R
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Offer Description We are seeking to appoint a Postdoctoral Researcher for a three-year position in machine learning emulators of ice-ocean processes. The role is part of PRECISE: Prediction of Climate