23 python "https:" "FUNDACIÓ ESADE UNIVERSITAT RAMON LLULL" Postdoctoral positions at Aalborg University in Denmark
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Andres Masegosa (arma@cs.aau.dk), Department of Computer Science. (please see: https://andresmasegosa.github.io/ . The project’s domain PI is Professor Jamal Jokar Arsanjani (jja@plan.aau.dk), Department
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(https://www.classique.aau.dk). CLASSIQUE will address a suite of fresh research challenges defined by the intersection of digital applications that have real-time requirements and quantum resources
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for applicants to demonstrate proficiency in at least one scientific programming environment such as Python, MATLAB, or R. Good understanding of hydrodynamic loading and wave–current environments (e.g., wave
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skills, with the ability to bridge theory and experimental data Experience with computational tools such as MATLAB, Python, and multiphysics simulation platforms (e.g., COMSOL, Ansys) Motivation to engage
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. Proficiency with CST Studio Suite, HFSS, and related full-wave EM simulation workflows. Competence in MATLAB or Python for numerical modelling, data analysis, and optimisation. Ability to conduct experimental
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field • Excellent oral and written English skills (Danish is a strong advantage) • Experience with Python, MATLAB, or C programming • Skills in hardware and firmware programming • Knowledge and experience
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characterization with scanning electron microscopy is a plus Experience with computational tools such as MATLAB, Python or relevant tools Ability to work independently and collaboratively in a multidisciplinary team
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. Your competencies We thus imagine that you: have a strong background in digital signal processing and machine learning; have substantial experience with scientific computing in Python/C++/ROS; know
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Computer Science and Mathematics. A background in algorithm design and implementation combined with solid programming skills (e.g., Java, C, C++, Python), is highly valued. Candidates are expected to contribute
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Neural Networks Deep Learning and Uncertainty Quantification Python and ML frameworks (TensorFlow, PyTorch, JAX) Reproducible and open-science practices Experience with geospatial, environmental