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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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prior experience in at least three of the following areas: Python programming Develop LLM-based tools to automate data connector generation for data ingestion. Design and implement a multi-layered storage
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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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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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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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: 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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experience with statistical tools (e.g. in R, MatLab, or Python) are expected. The team at DTU Aqua is highly international and knowing the Danish language is not needed. You must be available for boat-based