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discipline. Prior experience in any of the following is a plus but not essential: ultrasound or wave physics, numerical simulation, Python programming, and machine learning frameworks. Most importantly, we
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applicable, your experience of the below (desirable): FPGA prototyping and post-silicon validation. Python programming skills In addition for Research Associate Awareness of the research environment High level
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interest in computational chemistry. Familiarity with software development (Python, git) and supramolecular would be an advantage. Please note this post is subject to Dstl security clearances. Funding Notes
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, mechatronics, robotics, or applied physics Additive manufacturing / 3D printing and experimental mechanics Numerical modelling (FEA) and/or programming (Python/Matlab) Experience with 4D printing or SMPs is
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, and data analysis. Knowledge of advanced statistical methods or data visualisation (e.g., developing Shiny web applications). Experience with Statistical Programming using R and/or Python. Experience
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Science, Applied Mathematics or a closely related field. A strong mathematical background (probability, linear algebra, optimisation) and proficiency in programming (preferably Python/Matlab) are essential. Prior
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in programming for data analysis and algorithm development (e.g. Python, MATLAB). Strong analytical skills and the ability to critically evaluate technical and scientific literature. Excellent
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sciences. Prior machine learning or Python experience is a strong bonus, but not a must. We seek colleagues who enjoy coding, scripting and analytics, and are keen to push the boundaries of data-driven
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-and-route Be familiar with Python programming Have a working proficiency in English. (Finnish language is not required.) The following are considered an advantage Experience with FPGA prototyping
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(Python or equivalent) is desirable but not required. How to apply Applications should be submitted via the Physics PhD programme page. In place of a research proposal, you should upload a document stating