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(including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine learning techniques and experience with coding in Python is beneficial (but not a strong requirement) Applicants whose
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or willingness to learn programming languages (e.g., Python, R) for handling and analysing clinical data. Additional Requirements: Ability to work independently and collaboratively within an interdisciplinary team
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advantageous. Familiarity with space-grade hardware and radiation effects on electronics is beneficial but not essential. Strong programming skills in Python, C/C++, or HDL, along with analytical problem-solving
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familiarity with network management and orchestration tools. Applicants should also be proficient in programming languages such as Python, C, or Go, and have experience with network simulation or emulation
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. Under the guidance of the supervisor, the candidate will conduct experimental tests on composite samples to evaluate properties like crack propagation speed, GI,C and GII,C (mode I and mode II fracture
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tools like FEniCS and Python. Additionally, working on a high-impact, interdisciplinary project will strengthen problem-solving, critical thinking, and project management skills. The collaboration with
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software such as Matlab, R, Python or similar would be beneficial. The direction of the PhD is flexible and can be partially moulded to suit the strengths and interests of the successful candidate
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projects and staff, with an established international publication record, and success in leading research grants. Strong programming skills in a statistical language, such as R, Stata, Python or C/C++, etc
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knowledge of R or Python Molecular Biology experience (PCR, DNA extraction, pipetting) Experience working with museum samples would be a plus Further reading: https://onlinelibrary.wiley.com/doi/10.1111/mec
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this role, we are looking for candidates to have the following skills and experience: Essential criteria A working level knowledge of R and/or Python Some experience in independently designing a research