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experiences in working with remote sensing data, climate data and programming skills (R or Python) are desired. You enjoy working in an international team and you are keen on developing a key set of research
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collaboration Relevant experience with programming languages (preferably Python) You work independently, in a structured and reliable manner. You are communicative, flexible and able to work under pressure
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for challenging mathematical problems and interdisciplinary collaboration Relevant experience with programming languages (preferably Python) You work independently, in a structured and reliable manner. You are
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qualitative methods; some background in or willingness to learn computational social science methods as well as R and/or Python is highly desirable. Willingness to develop an ambitious empirical research
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, sociological...) to measuring beliefs, attitudes, and their relationship with shaping (online) behavior is desirable. Familiarity with data analysis in R or Python is required. Experience in study handling
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soil characterization techniques. A strong command of English is indispensable. Skills in R, MATLAB or Python are helpful. The effective exchange within the interdisciplinary collaboration will be
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discipline Strong interest in automation of process steps (Python, LabView, or similar... Experience in one (or more) of the following areas is desirable: programming, automation, synthesis of inorganic
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Proficiency in programming (e.g., Python, R) and related software tools. What We Offer Tuition waived and education at both institutions Employment contract according to 75% TVL 13 German civil servants pay
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diagnosis, and knowledge of the operation of helicopter systems. • Confident handling of Python and common data science tools. • Knowledge of high-performance computing and machine learning. • Fluency in
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programming languages such as C++, Python, MATLAB, or similar. Application Process: Interested candidates are invited to submit the following materials to alanwar@tum.de with email title "Ph.D. Position in