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Engineering, Physics or Materials Science Excellent English written and spoken communication skills The following skills are also highly desirable: Ability to program in Matlab, Python or similar Strong
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highly desirable: Ability to program in Matlab, Python or similar Strong laboratory-based skills Application Procedure Informal enquiries are encouraged and should be addressed to Prof Daniel Eakins
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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
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monitoring. Familiarity with tools such as Python, MATLAB, or embedded C would be advantageous. Most importantly, this project is ideal for applicants who are motivated to tackle real-world reliability
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programming skills (ideally C/C++ and Python/MATLAB or similar), good communication skills, the ability to work independently and a willingness to engage with industrial partners. To apply, please contact
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about to obtain) a PhD in the broad area of Computational Modelling applied to geochemical or biological systems, and be comfortable working routinely in modern programming languages (e.g. Python, Julia
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programming with Bash and Python is also required and previous experience of vertebrate and invertebrate genomes would be beneficial. The ideal candidate will be an independent researcher capable of managing a
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business datasets (e.g. ORBIS, Foreign Direct investment Data - UNCTAD) and appropriate experience with statistical software (e.g. Stata, R, Python). They will have a good understanding of, and interest in
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and computational abilities • Demonstrate excellent programming ability in languages such as MATLAB or Python • Excellent communication skills across multiple disciplines • Excellent academic
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assistantship. The ideal candidate will have a strong understanding of NLP, machine learning, and AI ethics, with proven skills in Python and frameworks like TensorFlow or PyTorch. Preference may be given