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(e.g., Python, R, Julia) Excellent written and spoken communication skills A demonstrated ability to produce high-quality, peer-reviewed research Position Details: This position will remain open until
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theoretical understanding of statistical machine learning methods relevant to the project: Bayesian learning, machine learning, spiking neural networks. Experience of programming (e.g. with Python) and data
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or multilayer networks, applied to biological data • Familiarity with HPC environments is highly desirable • Programming skills in R, Python or equivalent • Excellent communication skills in English
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well as to other tasks related to this research program in order to solve important problems. He/she will likely implement different algorithms in Python and potentially other programming languages. The postdoctoral
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technologies Proficiency in using Excel, Python, R or similar tools for engineering data analysis is preferrable Excellent written and oral communication skills Motivated self-starter with the ability to work
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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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skills in Python Demonstrated data analysis and visualization expertise Experience working in high-performance computing environments Familiarity with data analysis and visualization tools Preferred
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experience in embedded, real-time software in C/C++ and Python with several years of practice Experience in maintaining high-quality code on Github Ability to visualize experimental results Effective inter
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cell culture maintenance as evidenced in application materials. Experience with computational programming (Python, MATLAB). Project management experience. Contact Information to Applicants Carlo Barnaba
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analysis, and/or machine learning (e.g., Python, Scikit-learn, PyTorch, etc.) is also desired. A track record of publishing in peer-reviewed journals on related topics is also strongly preferred. Application