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Field
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Scientific area/research field: Educational Sciences Researcher profile: Recognised Researcher (R2) Admission requirements: Advanced knowledge and skills in data analysis and statistical analysis; Advanced
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at CU Boulder and Boston University Qualifications: • Ph.D. in Mathematics, Computer Science, Statistics, or closely related field (earned within the last five years preferred) • Demonstrated research
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Laboratory's activities cover a wide range of fields, from statistical physics to hydrodynamic turbulence, including mathematical physics and signal processing, as well as soft and condensed matter
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Artificial Intelligence (DSAI) is a multi-disciplinary department hosted under the Faculty of Computer and Mathematical Sciences established on 1 January 2025. DSAI will be at the forefront of cutting-edge
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 1 month ago
Sciences (14 ) Life Health and Medical Sciences (46 ) Mathematics and Statistics (11 ) Other Non-Science & Engineering (13 ) Physics (16 ) Science & Engineering-related (1 ) Social and Behavioral
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» Applied mathematics Mathematics » Statistics Researcher Profile Recognised Researcher (R2) Application Deadline 9 Feb 2026 - 22:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the
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of mathematics and statistics is required to analyze and interpret test results. • Knowledge and skill sufficient to maintain and operate standard instruments (fluorescence microscopes, pH meters, etc). Preferred
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License or Certification Required by Statute or Regulation None Preferred Experience, Skills, Training/Education PhD in Applied Mathematics, Statistics, Biostatistics, Data Science, Computer
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Econometrics (particularly applied micro, behavioural, or decision-focused modelling) Applied Mathematics, Operations Research, or Statistics Systems Engineering, Decision Science, or Complex Systems
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researchers. OCBE is internationally recognized, with interests spanning a broad range of areas, including high dimensional statistics, machine learning, mathematical modelling, causal inference, time-to-event