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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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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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programming (e.g. in python) are an advantage. Excellent oral and written English language skills. Strong collaborative skills, team spirit, yet the ability to work independently. Qualification requirements
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expected to hold: • A master degree in biomedical engineering • Excellent programming skills in Matlab and/or Python. • Experience in recording and analysis of electrophysiological signals is an advantage
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-based and farm models with a focus on biogeochemical and hydrogeological fluxes. Knowledge of greenhouse gas inventories (methane, ammonia, nitrous oxide) Proficient skills with scripting (R, Python) and
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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