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Cultural Studies, History, or related field Demonstrated expertise with large language models (fine-tuning, prompting, deployment) Strong Python programming with deep learning frameworks (PyTorch, TensorFlow
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. They will have experience working with bioacoustic and camera trap data and be familiar with deep learning methods, with a proven track record of training and applying audio signal classifiers. The successful
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modelling to address missing data and uneven data collection across different centres. Second, based on our recent deep learning biomechanics modelling work, you will perform cardiac biomechanical modelling
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the supervision and mentoring of junior researchers and doctoral students. It is essential that you hold a PhD/DPhil in Statistics, Biostatistics, Statistical Machine Learning, or a closely related quantitative
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. Experience in high-throughput sequencing data analysis and cluster/cloud computing. Proficiency in variant calling, single-cell DNA and/or RNA analysis, and machine/deep learning (preferred but not required
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experience at the time of application. Preference will be given to those with: (a) a PhD degree in GIScience, Geomatics, Computer Science, Big Data, Machine/Deep Learning, Artificial Intelligence or a
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liaison with vendors/suppliers. Work independently, as well as within a team, to ensure proper operation and maintenance of equipment Job Requirement Have relevant competence in the areas of Deep Learning
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Investigator (PI) to design and implement AI and machine-learning models for neuroimaging, blood biomarkers, and clinical datasets. • Develop deep learning architectures (e.g., CNNs, transformers, autoencoders
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focuses on single-cell genomics, biotechnology, and bioinformatics. The project involves transcriptomic and genomic profiling of single microbes. The post-doc will work on machine and deep learning methods
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. Wildfire, climate change, and ecosystem management Our lab works at the intersection of theoretical and empirical science. We value applicants who combine strong quantitative skills with a deep interest in