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- Charles University, Faculty of Mathematics and Physics
- Charles University, Faculty of Science
- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); yesterday published
- IRTA
- Institute of Czech Literature of the Czech Academy of Sciences
- Nature Careers
- Nova School of Business and Economics
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Field
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. Applicants with a strong background in optimization (including machine learning), algorithmic game theory, decision theory, computational social choice, social welfare, or fairness optimization are welcome
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a particular focus on Serbia Familiarity with theories of secularism/post-secularism, memory studies, or migration studies is highly desirable Ability to work independently and collaboratively in
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background in stochastics (probability theory and statistics) is desirable Good English as well as programming skills in R, python or C/C++ Pedagogical and presentation skills. German language skills are not a
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studies or another related field; doctoral studies already begun is an advantage Knowledge of 19th-century Czech and German literature in the Central European context and of contemporary literary theory
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open-source code (Python) that is high-performing and scalable to comprehensively quantify uncertainties using probability theory. This is where you will contribute: in the application of the developed
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technology experts work together to build a framework on open-source code (Python) that is high-performing and scalable to comprehensively quantify uncertainties using probability theory. This is where you
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of complexity theory, systems thinking, and simulation modeling. • Stakeholder management, marketing strategies, and customer satisfaction modeling. • Both basic and applied research, including contract research
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/or mathematical programming tools) applied to modelling agricultural and food policies and markets. Good knowledge of microeconomic theory and agricultural and food policies. Experience in using
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, Robotics, Computer Science, Statistics, or related discipline. Strong background in Machine Learning and Control Theory. Demonstrated experience in research projects with industrial partners. Excellent
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science or related discipline Experience and skills Experience in developing MLIPs, including good programming skills in Python and C, demonstrated via contributions to code repositories Experience with