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research, deep learning and biomedical image analysis are essential. Strong programming skills in Python and a keen interest in cross-disciplinary research are also required. Informal enquiries may be
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Language Models (e.g. Llama3, and Phi4) and Commerical models (e.g. Claude 3.7 and Gemini 2.5) to develop methods for generating simulation models of healthcare pathways in Python. The Health Service
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programming languages (e.g., R, Python). Successful applicants should be self-motivated, well-organized, and able to work independently and collaboratively. Excellent written and oral communication skills
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techniques (e.g., transcutaneous magnetic stimulation, near infrared spectroscopy, evoked potentials, electromyography) would be an asset Experience in utilizing programming/coding such as Python or Matlab
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spectroscopy, evoked potentials, electromyography) would be an asset Experience in utilizing programming/coding such as Python or Matlab would be an asset A clinical background (e.g., physical therapy
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(Python or similar) Prior experience in skin biology or inflammatory diseases is an advantage Excellence in both written and spoken English Passion for collaborative and interdisciplinary research Research
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proficiency in languages such as R and Python. Experience in GIS, remote sensing, and processing projected climate data. Proven ability to manage multiple tasks effectively, work collaboratively in team
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related field. Proficiency in one or more of the following: in vivo electrophysiology, two-photon imaging, animal surgery, behavioral design, programming languages (Python/MATLAB), and data analysis
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(Python, MATLAB) for processing and analyzing large or multimodal datasets (e.g., neural activity and behavior). Experience working with quantitative behavioral or electrophysiological data collection
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with experience in One Health or climate-health research. Proficiency in systematic reviews, survey methods, and/or causal inference is essential, along with programming skills (e.g., in R or Python