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Field
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. The goal is to build foundation models capable of learning from richly structured or semi-structured data where traditional graph neural networks may fall short, enabling better representation, inference
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or Postdoctoral position (m/f/d) - Interpretable Machine Learning for Catalytic Reaction Network Discovery. A full-time PhD or Postdoctoral position is available in a collaborative Max Planck research
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coefficient modeling. Experience in integrating modeling with leaching and separation processes for scale-up. Advanced data interpretation using electron diffraction, dendritic growth modeling, and REE behavior
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, instrumentation, modeling, and data science Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field(s) of materials science, physics, computational science, or a related field
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level of detail extracted from these experiments. As part of this role, you will work closely with other researchers to translate these experimental results into our numerical models, helping to improve
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to the 4th February 2026. You will be investigating the safety and security implications of large language model (LLM) agents, particularly those capable of interacting with operating systems and external APIs
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We are seeking to appoint a Researcher in Infectious Disease Modelling. You will be an integral part of the Pathogen Dynamics group at Oxford, led by Christophe Fraser, where the team focuses
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in this kind of environment will result in models too large to be handled and too instable to be solved. Data-driven approaches need to be used in addition to enrich the physics-based models
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Type of Position Staff Position Time Status Full-Time Required Education PhD Required Related Experience Experience with molecular biology techniques such as PCR/RTPCR, gel electrophoresis, DNA/RNA
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Application Required Documents Curriculum Vita Name and Contact Information of References Letters of Interest Number of References: 3 To start the Online Application process for this position, click the "Apply