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of thesis by the start date) in economics, psychology, or a closely related discipline. Strong programming skills in Python, Stata, or R. A solid foundation and interest in behavioral and experimental
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: PhD in computer science, machine learning, operations research, transportation engineering or a related field. Programming skills in C/C++ and Python, along with experience working with simulation
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digital co-simulation platforms (e.g., Modelica-Python/Simulink) Applying machine learning and data-driven approaches to enhance the operation of district heating substations Participating in course
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or related field. Expertise in graph machine learning and demonstrated experience in multi-omics data integration. Strong programming skills in Python and its scientific and graph ML libraries (numpy, pandas
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co-simulation platforms (e.g., TRNSYS-Python) Implement and test AI-enabled smart energy management strategies in real-world settings Conducting in situ measurements, including planning, setting up
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on the platform CUDA for parallelization of the computation over several GPUs’ cores, and has interfaces with Matlab and Python for ease of use. However, powerful as it is, MagTense is at present limited in its
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considered an asset in these positions. Applicants must also be able to demonstrate excellent ability to code with or learn computer programming languages, such as C++, C#, Python, and/or Matlab
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modelling, preferably WRF Experience of scientific programming and running code on HPC systems Experience with Fortran, Python and Linux Shell Any of the following is advantageous but not essential
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related field Experience with Earth System or biogeochemical modelling Strong programming skills (e.g., Python, R, MATLAB) and experience with advanced machine learning modelling A strong interest in
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machine learning, statistics, time series analysis or similar field Demonstrated ability to conduct outstanding research with measurable impact Experience with Python, especially related to machine learning