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Field
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: experience working with spatial omics or spatially resolved data in tissue experience applying AI or machine learning methods to digital pathology or histology data experience analysing kidney or transplant
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We are seeking a postdoctoral researcher with a curiosity-driven record who works at the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy
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Science Statistics / Biostatistics Applied Mathematics Data Science Demonstrated expertise in modern machine learning, including at least one of the following: Deep learning (e.g., transformers, sequence models
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modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics, and metabolomics. Working closely with senior
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and high-speed microscopy with AI and machine learning to form stable liposomes from libraries of (novel) phospholipids that can robustly encapsulate cell-free gene expression systems. You will then
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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modeling, machine learning, • Experience in human electrophysiological research is a plus, experience in intracranial human research large plus, • Knowledge of cognitive system is a plus, knowledge of
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publications prior to the panel interview. In addition to further excelling your skills in Computer Vision/Big Data/Machine Learning analyses, this opportunity enables you to: - Work closely with clinicians
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will begin from June 2026. Education and Background PhD degree in a relevant quantitative discipline such as Bioinformatics, Statistics, Mathematics, Data Engineering, or Biomedical Engineering
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scale. Increasingly, our work integrates AI and machine learning approaches to process and interpret large and complex Remote Sensing datasets. When joining our group, you will also join the wider and