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Implementing labeling functions for supervised learning Analyzing microstructure patterns (e.g., spread crossing opportunities) Required skills Strong programming skills (Rust and/or Python) Experience handling
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engineering, or another related field Strong knowledge of Machine Learning theory and methods, and related Deep Learning approaches Excellent knowledge of programming in Python and scientific libraries used
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experience • experience with physiological data (e.g., cardiac activity), motion capture, or biosignal analysis • experience with statistical software or programming tools (e.g., Julia, MATLAB, Python, R
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skills in python Proven software engineering skills Excellent written and verbal communication skills in English and able to work collaboratively In addition, according to the system of the University
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data processing, single-cell data processing, and Matlab, R, or Python, and scientific illustrations will be an advantage. Finally, the ideal applicant also has high proficiency in spoken and written
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., Python, Matlab, Fortran, C). Ability and willingness to learn new things. Good communication skills. See also the requirements of the University of Oulu Graduate School (UniOGS) . Salary The position is
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of physics related to electrodynamics and magnetohydrodynamics, geosciences, and solar physics. Experience in numerical modelling, knowledge of programming languages (e.g., Python, Matlab, Fortran, C). Ability
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PCB/CAD design Programming skills (Python / C++ / MATLAB) Basic knowledge of signal processing Highly motivated to design, implement and test novel ideas and concepts In accordance with Marie Skłodowska
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skills and experience with tools such as MATLAB or Python Life cycle assessment (LCA) Software related experience on system dynamics modelling, GIS, and energy simulations Research writing and publications
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
science, applied mathematics or a related field. Programming proficiency in Python is required, and hands-on experience with ML libraries such as PyTorch is expected. Theoretical understanding and experience with