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for translational biomedical research, with extensive expertise and infrastructure in drug discovery, cancer biology, pharmacology, animal models, imaging, and therapeutic development. The Skaggs School of Pharmacy
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degree in Computer Science/Computer Engineering. Possessing a Master’s or PhD degree will definitely be advantageous. Knowledge of machine learning, pytorch, huggingface etc... Knowledge of image
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with departmental and university policies. Required Qualifications* PhD in Biostatistics, Statistics, Mathematics, Computer Science, or a related quantitative field by the time of appointment Strong
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scalable way. This project aims to solve this by combining different kinds of data - structural, functional, and causal - into a single AI-centred computer model. We focus on the larval zebrafish, a small
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meetings. To undertake any other duties relevant to the programme of research. Job Requirements: PhD degree or at least 8 years working experience in Computer Engineering, Computer Science, Electronics
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-based processing of geospatial data; reproducible research workflows, scientific data management or FAIR data principles, e.g. Github; science communication or visualisation of spatial and environmental
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for developing and using systems to phenotype root systems in greenhouse and field settings under the guidance of research mentors. Build skills in root image processing and other data analysis activities using
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. Desired Skill Sets A PhD in Engineering, Math, Physics, Computer Science or a related field. Strong programming and computational skills. Experience in AI development, mathematical modeling or data analysis
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, clustering and classification of extensive marine-based image archives, characterisation of change in multi-year surveys and adaptive mission planning for multi-vehicle systems. We undertake marine surveys
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characterization, scientific computing, and artificial intelligence. Applicants should have: A Ph.D. in mechanical engineering, materials science and engineering, applied physics, computational science, or a closely