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participation in conferences and events. Desirable It is desirable that the candidate has a Masters or PhD in electronic engineering, computer science or equivalent Fluent in Python and Python Libraries: Scikit
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-level optimisation using TRNSYS and MATLAB/Python. The associate will use advanced characterisation (e.g., DVS, porosimeter, DSC/LFA) to develop and assess adsorption composites, and apply CFD to analyse
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skills (Python, TensorFlow, PyTorch, scikit-learn, etc.). Excellent stakeholder engagement and communication skills, with a record of working with SMEs or innovation-focused organisations. Desirable
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(NFQ Level 8) or Master’s (Level 9) in a relevant discipline plus 3–4 years applied professional experience in AI/ML development. Strong programming and applied AI/ML development skills (Python
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Python, using GPUs), with the precise balance determined by the candidate’s background and interests. The mathematical tools involved will include matrix analysis, optimization, backward error analysis
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subject by the start date of the appointment Good programming skills (r, Fortran, Python) Familiarity with eco-evolutionary optimality approaches to modelling vegetation Experience with working with large
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programming skills (preferably Python and C/C++) Expertise in bioinformatics of noncoding RNA Proven ability to publish in leading international journals Excellent communication skills and ability to work in a
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to the proposed area of research. You should have experience in finite element modelling and data-driven multiphysics approaches. Fluency in Python, Fortran, MATLAB and/or C/C++ and prior work with common finite
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, neuroscience or computer science Proficiency in Python, R, Matlab, or another relevant programming language Expertise in integrated analysis of behavioural and imaging data. Experience working with children in
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: Relevant domain knowledge relating to cardiac electrophysiology Excellence in Python software development for scientific computing A strong knowledge and experience of database software including SQL Prior