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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
demonstrated proficiency with computer coding, such as Python, MATLAB, R, and expertise in statistical modelling. · Experience in designing, planning, and conducting experimental procedures, including
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using digital learning tools such as R, Python, Stata or Matlab, and has strong data skills. Holds, or will soon complete, a doctorate in a relevant discipline. Desirable qualities include experience
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the use of databases or knowledge in data processing and statistical metrics*; 2. Proficiency in English*; 3. Knowledge of Python, MATLAB or R programming languages*; * mandatory requirement Work plan: The
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modelling of cognitive processes. Fluent in statistical code in either R, Python, or Matlab. The advantage is Previous work on social cognition, decision-making, moral psychology and related topics
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learning tools for analysing healthcare data; Proven competence in mathematics and programming data analysis methods in Matlab or Python. Desirable: An interest in the application area of healthcare
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., in C++, Python or Matlab. Who we are The successful candidate will be hosted by the Section on AI & Sound. This section is led by Prof. Jan Østergaard. A dedicated supervisory team composed of experts
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transport measurements Familiarity with the theory of magnetism Proficiency in MATLAB/Python and LabVIEW for data acquisition and analysis Good written and oral communication skills Ability to work
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non-human primates and/or background in electrophysiology of the visual system are preferred. All candidates must possess strong quantitative skills (e.g. Matlab, C++, Python). The term
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design, data analysis, and programming (e.g., SPM, MATLAB, Python, R, etc.) Strong scientific writing skills Excellent organizational and communication skills Willingness to work in an interdisciplinary
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programming skills (for example MATLAB and/or Python) are highly preferred but not required. A two-year commitment is required. ADDITIONAL JOB DETAILS: The Translational Research in Affective Disorders