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hands-on experience in molecular cloning, cell culture systems, mouse models, and interest in liver disease biology. Experience with R or Python and the computational analysis of next-generation
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of Unix systems (GNU Linux) and keen to gain hands-on experience in Networks and systems Machine Learning knowledge is a plus Strong analytical and programming skills are required (Python, Matlab, Golang
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into account as disruptive events, and which strategies can be derived from this for a resilient system design. Your contribution to scientific analysis: Further develop existing energy system models in Python
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(agent-based modeling, differential equations) or machine learning tools. Good programming skills in one of the following programming languages: R, Python, MATLAB, or similar; Excellent English language
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. Strong knowledge of quantitative and/or computational research methods, ideally in econometric analysis or optimization and simulation models. Preferable knowledge in Python and STATA. A collaborative team
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particular in deep learning, LLM, digital hardware design, embedded systems, audio processing; Proficiency in deep learning frameworks (e.g. PyTorch) and programming skills (SystemVerilog, Verilog, Python, C
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include: Developing the model using open-source Python software Planning and conducting experiments Analysing teardown reports and experimental data Validating and improving the model Publishing results in
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for this position) Experience with programming languages (e.g., Python, MATLAB) and simulation software Excellent academic a dynamic, creative and pioneering professional attitude with a willingness to
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but not mandatory). A strong interest in materials simulation, quantum materials, and condensed matter physics. Experience with Python. Fluency in English is required. Finnish language is not required
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experience of data science analytical packages and R or Python would be advantageous. Funding The project is funded by the UKHSA and Nottingham University Business School. As a UK public body, UKHSA can only