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responses and microbial persistence. Learn to design, train, and iteratively refine machine learning models to learn distinguishing features of true microbial contaminants versus host-derived and process
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-identification, and version control. • Collaborate with clinicians, engineers, and data scientists to integrate imaging biomarkers into predictive and diagnostic models. • Contribute to study design, IRB
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scalability of simulation workflows via: Parallelization and performance engineering GPU/accelerator optimization Algorithmic innovation Experience applying machine learning or AI to molecular simulation
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a highly motivated Postdoctoral Associate at the Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology in Jupiter, Florida. The area of our research focuses on coronary
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learning analytics, with a focus on the deployment of eye-trackers or fNIRS devices; creating end-to-end prototypes of AI systems, including LLM integration, backend development, and interface design and
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human health. Within this mission, the Iorio Group works at the intersection of computational biology, functional genomics, and precision oncology, integrating machine learning, large-scale CRISPR
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relevant links to Research Centres. The Associate is expected to generate breakthrough ideas in the assigned area of research, as well as to carry out research in line with the project plan. The successful
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may also support intellectual property development and the translation of methods into deployable solutions. Grow your skills You will enhance your scientific and professional skills by: Designing and
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learning (RL) and deep reinforcement learning (DRL) for autonomous process management, dynamic resource distribution, and real-time decision-making. Design and deploy digital twins for integrated chemical
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asynchronous AI-led chemical optimisation across chemistry laboratories¿. This role sits at the intersection of robotics, machine learning, and chemistry, aiming to develop robotic systems that work