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Field
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‑EM) Computational protein modelling and design Protein biochemistry and biophysics Interest in and capacity for development of bioinformatics methods and programming in Python Academic Eligibility
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areas: AI/ML, image processing, molecular modeling and docking Strong experience in Python and C++ programming (knowledge of Fortran is a plus) Strong interest in interdisciplinary research bridging
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evaluate usability of system architectures such as Retrieval-Augmented Generation (RAG) for data retrieval and knowledge inference - implementation of your machine learning pipeline in Python (using e.g
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• Programming skills (e.g., Python, MATLAB, R) • Experience with AI/ML methods or power system modelling Conditional Offer The award of the PHAETHON PhD Studentship is strictly conditional upon the candidate’s
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, ELT/ETL pipelines, AI/ML, Unity and Unreal Engine development, shading, real-time simulation, immersive scientific visualisation, digital twin, C/C++, Python are desirable. Applications from both UK and
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. Our software is built primarily in Rust, with R and Python parts to support bioinformaticians. Our web frontend is also developed in Rust (web assembly) – all to support fast computing and handling
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(e.g. PACT). Skills in data analysis (e.g. Python, MATLAB, ImageJ) will be considered an asset. Specific Requirements A scientific scholarship from the National Science Centre (NCN) may be awarded to a
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Engineering, or a related discipline - Solid understanding of fluid dynamics and/or electromagnetism - Programming experience (preferably Python) - Interest in machine learning and scientific computing
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for seeking the position. Extensive experience with Python, Matlab, and R, and good UNIX knowledge are essential skills, as well as familiarity with biological omics data analysis techniques. Experience with
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data (nationwide LiDAR coverage at 50 cm resolution). The candidate will perform quantitative morphometric analyses of landscapes and river networks near suspected active faults using GIS tools, Python