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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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. 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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population surveys and randomized trials). Responsibilities: Utilize Python, R, and containerization (Docker, Kubernetes) to run computational analyses and automated data pipelines. Optimize data processing
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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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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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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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degree and sufficient work experience would also be considered. Proficiency in Python for data analysis. Experience interfacing databases and R scripting will be an advantage but not required. Familiarity
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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
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technology Experienced with engineering coding in Python and/or MATLAB Technical knowledge of camera hardware, such as RGB and thermal cameras Hands-on knowledge of drones and their operation, A1/A3 license
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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