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-field methods) Multiscale mechanics and microstructure-property relationships Python/C++/Matlab-based simulation and data analysis Industry-facing research and technology transfer You will also benefit
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will be an advantage if candidates have an interest in optimisation, control and computing systems, model checking, mathematical logic and good programming skills, ideally in MATLAB, Python and/or C/C
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). Experience in numerical modeling and data analysis. An interest in groundwater contamination, risk assessment, and sustainability. Programming experience (Python, MATLAB, or similar) is desirable but not
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in working in public health or epidemiology or similar is desirable. Knowledge and evidenced experience of data science analytical packages and R or Python would be advantageous. Funding The funding
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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
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laboratory-based skills Programming skills (Matlab, Python, or similar) Applicants with a good 2.1 degree are also encouraged to apply if they can demonstrate excellent laboratory skills through previous
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degree or MSc degree (Distinction/Merit) in engineering, computer science, or other closely related fields. Experience with ROS and proficient programming language skills (C++, Python, MATLAB) would be
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of challenges of building large-scale systems. Programming skills in Python. A good Bachelor’s Hons degree (2.1 or above or international equivalent) and/or Master’s degree in a relevant subject (physics
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understanding of challenges of building large-scale systems. Programming skills in Python. A good Bachelor’s Hons degree (2.1 or above or international equivalent) and/or Master’s degree in a relevant subject