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Field
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, tissue sections, RNA/DNA, tabular data) for predictive modelling using software such as Python Documented experience of neural networks, image processing, deep learning algorithms, and data visualization
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Education, STEM Education, Statistics, or a closely related field. Experience conducting quantitative analysis using statistical software such as R or Python. Experience conducting educational, social science
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team and train others Proficiency with computer programming (e.g., MATLAB, Python, R, etc.) Desirable Qualifications: Experience using preprocessing and postprocessing pipelines for resting state
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, or portable robotic platforms Experience in programming and configuring control systems for automation and robotics, including relevant programming languages such as PLC, Python, C/C++, MATLAB, ROS
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learning; software development Preferred Qualifications: Excellent academic writing ability on quantitative topics Familiarity with relevant software environments (e.g., R, Python, SPSS) Expertise in
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or a closely related field, and you will have a background in crystallisation and solid state characterisation. Knowledge of databases, and python coding is a must. The key responsibilities
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, machine learning, statistics and programming skills (R and Python) is preferred. Record of peer-reviewed publications. Knowledge in one or more of the following areas is desirable: single-cell profiling
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models, transformers, representation learning, contrastive methods). Solid experience with Python and Pytorch and good command of software development tools such as GIT. A good track record of authoring
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Qualifications: Ph.D. (within 0–5 years) in computational bioscience, computational biophysics, computer science, or a related field Strong programming skills in C++, Python, or similar scientific computing
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using a range of specialised research techniques. Good knowledge of the R statistical programming language. Programming experience in C, C++ or Python is desirable. Excellent verbal and written