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on priorities, and work both independently and as part of a team. PREFERRED: experience with molecular machine learning, biological data, chemical data, clinical data, materials data, graph-based methods
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: • Multimodal data integration: combining structured data (graphs, ontologies, relational databases), unstructured text (scientific literature, clinical reports), and molecular or numerical features into a
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, charts, graphs, and spreadsheets. Manage confidential information with discretion to prevent adverse operational or personnel impacts. Represent DHTS on internal or external committees as assigned. Provide
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scholars/fellows on the status of research. Collect and log laboratory results and/or survey data. Evaluate and perform data analysis using graphs, charts, or tables to highlight the key points
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graphs and network medicine • Translational data science for therapeutic discovery Primary Responsibilities: The Postdoctoral Research Associate is expected to lead and contribute to independent and
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and generate graphs using tools such as GraphPad Prism, MATLAB, Python, Fiji, and Imaris. • Generate scientific figures using BioRender and Adobe Illustrator. • Maintain a detailed lab notebook and
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design discussions Perform literature reviews Prepare reports Compare data and historical records for trend verification Develop reference files, comparison charts, and graphs on research data Assist with
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(Neural ODEs), and broader LLM applications. • Knowledge Graphs: Developing Knowledge Graph architectures to map complex interdependencies and uncover insights across multi-sector systems. Explore how
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through strategies such as reinforcement learning (RL) and innovative frameworks like the "graph of thoughts". We are firmly in the "Age of Computation", where breakthroughs in AI are synonymous with
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research in discrete mathematics, deliver outstanding teaching, and support the development of undergraduate and postgraduate students. Research areas of interest include combinatorics, graph theory, design