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, computational science, or a related field is required, along with technical competency in computational methods or engineering simulation, supported by a strong mathematical background and practical experience
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degree in a quantitative or computational field and have strong Python skills. Experience with AI or NLP methods, including LLMs cloud platforms, containerisation, APIs, relational databases and data
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Engineering or a closely related discipline. You will have demonstrable experience in one or more of the following areas: Finite Element Analysis, Computational Fluid Dynamics, Discrete Element Method, Multi
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methods can be highly effective in supporting aquatic macroinvertebrates and plants. Despite increasing literature and interest in pond creation and restoration (hereby collectively referred to as pond
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: • Knowledge of fluid dynamics, especially experimental methods in atomisation and sprays. • Programming experience (e.g. Python, MATLAB or similar). • Experience with data analysis, machine learning
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of farm animal welfare in educational settings. The successful candidate will receive interdisciplinary training in animal welfare assessment, qualitative and quantitative research methods, and stakeholder
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biotechnical methods to improve colony health and pollination-relevant outcomes. The project will investigate whether hive volatile organic compound (VOC) profiles shift with Varroa infestation intensity and
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; Mechatronics; Agricultural Engineering; Mechanical Engineering; Electrical/Electronic Engineering; Computer Science; Control Engineering, or a related discipline Desirable: • Programming in Python or C
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Adams e-Recruitment programme at http://jobs.harper-adams.ac.uk submitting your CV and a personal statement outlining your suitability for the role. Your personal statement should clearly demonstrate how
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queries or questions or for an informal discussion, please contact Laura Harper via e-mail lharper@harper-adams.ac.uk Application Procedure: Please apply online via the Harper Adams e-Recruitment programme