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-level data on single cell level, R/Bioconductor and Python/Tensorflow will be useful but is not a requirement. An experimental researcher with an interest in methodologically driven cancer research
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placement locations. Advanced metaheuristic optimisation algorithms, implemented in Python and interfaced with DIgSILENT PowerFactory, will be developed to determine the most effective PST locations and
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take on administrative tasks in research, teaching and administration. Your profile: Completed Master's / Diploma degree in the field of Astrophysics Extensive programming knowledge (Python) Excellent
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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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languages for data analysis such as Python, C++ and Matlab. Knowledge with various microscopy instrumentation such as dual beam focused ion beam/scanning electron microscopy (FIB/SEM) Behavioural Competencies
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, and skills in modelling & programming tools such as SINCAL, PowerFactory, OpenDSS, PSCAD, Python, Matlab, R, or Julia would be desirable. For full details about this role, please review the Position
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electronic engineering. Proficiency in programming languages such as Python, C++, or MATLAB. Strong problem-solving skills and the ability to collaborate in interdisciplinary teams. Excellent command
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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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into longitudinal studies and in using functional MRI and scripting-based languages (e.g. Matlab, R, Python). They must also have experience of conducting research with human participants and of performing highly
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analyse large, multidimensional 4D STEM datasets. Develop or adapt software tools (e.g. Python, MATLAB) for image reconstruction, phase mapping, and quantitative analysis of ferroelectric domain wall