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engineering Machine learning or AI methods (e.g. anomaly detection, classification, regression, time-series modelling) Programming skills (e.g. Python, MATLAB or similar) Experience with industrial systems
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programming languages like Python or Matlab environment. Knowledge for programming (python) would be a plus for the force curves interpretation since some codes have been developed for the 3D -AFM data analysis
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a related field who bring hands-on expertise in in vivo calcium imaging or electrophysiology, along with strong data analysis experience in Python and/or MATLAB. Candidates who combine quantitative
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(e.g., Python, Julia, Fortran, C++, MATLAB) and experience with high-performance computing environments Demonstrated publication record in reputable peer-reviewed journals Excellent written and oral
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., MATLAB, Python) is required. Experience with machine learning is highly preferred. Ability to work independently and as part of a team. Key Requirements for PhD: Hold a Bachelor's degree with outstanding
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interest in learning, adaptation, and dynamical systems in physical contexts Experience with analytical and\or computational modeling. Proficiency in numerical methods and coding (Python, JAX, MATLAB
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Expertise in FEM software (ABAQUS, ANSYS, SAP2000) and coding (Python/MATLAB). Professional engineering licensure (HKIE/CEng) or eligibility is a plus. Candidates for Professor or above should have
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semiconductors. You should have experience working in a laboratory environment, along with basic programming and data analysis skills (Python, MATLAB, LabVIEW). High motivation, very good English or German skills
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techniques Experience with data analysis using, e.g., Origin, Python or MatLab Programming skills, e.g. proficient with Labview or Python Language requirement: Good oral and written communication skills in
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closely related field. You are skilled in data-driven modelling methodologies, data analytics, and programming (Python, MATLAB, C/C++) You have a keen interest in real-time systems and digital twin