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Field
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for implementing the model as a computer simulation and analysing it within a health-economics framework using standard computational techniques. The post-holder will also be responsible for writing up the findings
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. Desirable: Proficiency in scientific programming (e.g. Python) and familiarity with data science and machine learning techniques. Experience with geochemical analytical techniques and working in a laboratory
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: Computer Architecture Algorithms and Optimization Health Research Human-Computer Interaction Machine Learning and ML Foundations Machine Perception Natural Language Processing (including Information
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Profile PhD in Computer Science, Data Science, Machine Learning, Engineering, Biomedical Informatics, Bioengineering, or a related field Proficiency in python programming Strong expertise in machine
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simulations using DFT (particularly of surface processes); kinetic Monte Carlo simulations; molecular dynamics simulations; classical and machine-learned force fields. Highly developed skills in scientific
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Language Processing (NLP) with a focus on large language models, deep learning, and multi-modal machine learning. The researcher will work on the project KAMAL Health: Knowledge-Augmented Multi-Modal Arabic LLMs
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, single-cell analysis, and machine/deep learning (preferred but not required). Strong programming and statistical skills (e.g., Python, Perl, R, Bash). Track record of first-author research papers. Strong
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cerebral organoid models to study the impact of environmental exposures on metabolostasis and proteostasis Build and validate machine learning models (in collaboration) for molecular data analysis and
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The Distinguished Research Fellowship Program seeks PhD graduates from underrepresented groups for postdoctoral experience and training in the School of Engineering and Applied Sciences . The aim of the program is to
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Essential Qualifications and Experience: PhD (or near completion) in political science, social sciences, public/global health, or related field Strong understanding of climate change and health, particularly