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Field
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field. A background in organic chemistry, and/or high-throughput experimentation is desirable. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is
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field. A background in organic chemistry, and/or high-throughput experimentation is desirable. Proficiency in programming languages (Python/MATLAB) commonly used in machine learning applications is
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modelling and simulation techniques and software packages would be an advantage. Programming skills in languages such as Python, C++, MATLAB, are desirable, as is an awareness of machine learning or other AI
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the coupled aerodynamic, structural and thermal analysis of interface regions, for example between fins and fuselage, in hypersonic vehicles. This will involve the use and augmentation of in-house python-based
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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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, or the equivalent qualifications gained outside the UK. Experience in coding in both Python and R is essential.
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(e.g., Python, or MATLAB, or C++; knowledge in ROS). Interest in robot control, learning, manipulation, and task planning. Preferred Experience with robotic hardware or simulation tools. Publications in
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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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have experience conducting both qualitative (e.g., knowledge of interviews, thematic analysis, grounded theory, or IPA) and quantitative (e.g., experiments, surveys, skills in SPSS, R, or Python