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Field
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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and
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experimental data from both literature and in-house experiment results Use state-of-the-art machine learning models to develop a multi-scale droplets evaporation model Assists in co-supervision of Final Year
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Apply Now How to Apply To be considered for this position, applicants should submit their materials to Interfolio https://apply.interfolio.com/179185 Cover letter (1-2 pages) which includes a
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for developing machine learning models for the automatic identification of species from images collected through electronic monitoring systems (Work Package 3 – Bycatch Monitoring). The candidate will be involved
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/Research Fellow(SRF/RF) to carry out research in robotics and machine learning by exploring cutting-edge approaches such as learning-based robot perception, adaptive control with reinforcement learning
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publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential. Additionally, the candidate should possess an excellent
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University More Jobs from This Employer https://main.hercjobs.org/jobs/21774562/postdoctoral-research-fellow-in-statistical-machine-learning-and-biomedical-ai Return to Search Results
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, computational biology, bioinformatics, biostatistics, machine learning, or a related discipline. ● Strong background in at least one of infectious disease modelling, phylogenetics, or phylodynamics (background in
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Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI – AI/CS-Oriented Role
across visual, textual, and biomedical data modalities. While one major application area is biomedical and neuroscience imaging, the research will emphasize core AI challenges in representation learning
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Postdoctoral Research Fellow in Multimodal Foundation Models and Biomedical AI – AI/CS-Oriented Role
across visual, textual, and biomedical data modalities. While one major application area is biomedical and neuroscience imaging, the research will emphasize core AI challenges in representation learning