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optimisation, hands-on experience from modelling membranes with CFD software tools such as ANSYS Fluent, and proficiency in programming languages such as Python, MATLAB, or similar. You must contribute
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have: Experience in Python Experience with deep learning frameworks Interest in design and user test of explainable AI systems Interest in EEG High level of motivation and innovation Excellent
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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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proficient in ROS/ROS2, Python and/or C++/C# Knowledge and/or experience within one or more of the fields of acoustic sensing, hydrodynamics, and machine learning is a plus. You have strong communication
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areas: Scientific programming using Python Data analytics and machine learning techniques Wind energy systems, operations, or related topics In addition, you should be able to work efficiently as part of
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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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. Responsibilities and qualifications Qualifications: PhD degree in Engineering, Physics, Computer Science, or Applied Mathematics. Proficiency in scientific programming with Python. Excellent oral and written
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areas: Knowledge of computer science and operations research Familiarity with renewable energy systems and their challenges Proficiency in programming languages such as Python or Julia Strong problem
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equivalent to a two-year master's degree. Additional qualifications include: Good programming skills in Python, Julia, R or similar, and familiarity with C, C# or C++. Curiosity and interest in future urban
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or optimization. Proven experience with programming and data analysis tools. Fluency in Python, including experience writing data analysis scripts and model training code. Experience with scientific computing and