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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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field. Experience in the following is essential: single-cell fluorescence microscopy, microfluidics, image analysis, and machine learning (as applied to biological imaging). Python and MATLAB programming
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: single-cell fluorescence microscopy, microfluidics, image analysis, and machine learning (as applied to biological imaging). Python and MATLAB programming, especially in image analysis, are also essential
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College of Chemistry and Molecular Engineering, Peking University | Streatham, England | United Kingdom | about 4 hours ago
the discipline and of research methods and techniques to work within established research programmes. Applicants will have coding skills in Python, PIP, JSON and HTML and will be experienced in using MongoDB
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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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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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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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. Proficiency in Python and/or machine learning applications for data analysis. Ability to work independently and manage multiple research activities. Experience contributing to academic publications and
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in the annotated and non-annotated genome space. Writing optimised R- or python-based scripts and train group members on using these to analyse their own datasets optimally. Writing scientific papers