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level, developing and employing machine-learning tools for predicting antibody-epitope binding. In silico antibody design is a long-standing computational and immunological problem. Improving
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models of therapeutic response using machine learning combined with Fourier-Transform Infrared Spectroscopy (FTIR) applied to blood, saliva, and tumor tissue samples. Requirements: PhD completed by
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environments) remains an open frontier. The new MIT Multi-agent AI Postdoctoral Fellowship Program at Schwarzman College of Computing (MIT MAPS) brings together cutting-edge methods in machine learning
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
: PD&PEWER Level A&B Postdoctoral - Research Fellow _ CSS.pdf This position will provide opportunities to: Conduct cutting edge research in machine learning, AI and algorithms, such as but not limited
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical technology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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8 Oct 2025 Job Information Organisation/Company INESC ID Research Field Engineering » Biomedical engineering Engineering » Computer engineering Researcher Profile First Stage Researcher (R1
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devices. Minimum requirements: Advanced knowledge of machine learning models and Python tools for signal processing and machine learning. General knowledge of system architecture and APIs. Previous
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techniques, or tight-binding approaches. Proficiency with major simulation packages such as ASE, Quantum ESPRESSO, VASP, CP2K, or LAMMPS, and their Python interfaces. Working knowledge of machine learning
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. This project involves the development and application of interpretable machine learning methods to uncover allosteric regulation of disordered regions in the dynamics of G-protein coupled receptors to enable
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-binding approaches. Proficiency with major simulation packages such as ASE, Quantum ESPRESSO, VASP, CP2K, or LAMMPS, and their Python interfaces. Working knowledge of machine learning techniques in