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strong background in shape modelling, deep generative modelling (diffusion/transformers), or multimodal representation learning. You have strong programming skills, especially in Python, and preferably
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with proven advanced experimental capabilities and excellent programming skills (e.g. C++, ROS, Matlab, Python etc.). You should have a strong vision to evaluate and demonstrate the research findings in
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, Python, and SAS or Stata) • Demonstrated expertise in causal inference and high-dimensional risk adjustment/predictive modeling, experience with Medicare claims data • Clear scientific writing and
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learning, medical image computing, biomedical engineering, medical physics, or related field Strong Python and PyTorch experience Solid publication record and ability to communicate research results
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and/or cognitive neuroscience, preferentially in the field of attention and memory Excellent research methods knowledge and skills Solid programming skills (e.g., MATLAB, R, Python) Demonstrated
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for gastrointestinal (GI) cancers. Working within the O’Neill lab, you will play a central role in the collection, processing, maintenance, and characterisation of tumour and blood samples using a perfused culture
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of the microgrid ii) develop the optimal sizing method for microgrid using programming software like Python or Matlab, implement it for case study areas, and iii) prepare research reports and contribute to project
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-completed PhD (within the last 0-5 years) in field of physics, engineering, or a closely related field Demonstrated programming proficiency in C/C++, Python, or another scientific programming language
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programming languages for data analysis (e.g., R, Python). Experience with mass spectrometry-based metabolomics approaches, including LC-MS/MS. Experience operating, maintaining, and troubleshooting LC-MS/MS
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advanced signal processing and time–frequency analyses of neural recordings. Develop and implement computational pipelines using MATLAB, Python, or similar platforms. Lead manuscript preparation for peer