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Field
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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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: Strong understanding of statistics, probability, optimization, and linear algebra. - Machine Learning: Deep learning, probabilistic modeling, generative models, etc. - Programming & Software Development
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will possess a relevant PhD or equivalent qualification/experience in a relevant field of study (e.g. data science, AI, machine learning, statistics, physics). They will be motivated to solve problems
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balance of supervised investigation and work experience in a learning environment that will expose the participant to activities across the drug development process. We are seeking scientists from U.S
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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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, and needs to be responsible for reporting progress and delivering outputs to the project. The PhD position is linked to NTNU Aluminium Product Innovation Center (NAPIC) and MANULAB – Norwegian
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transcriptomic data, that will be integrated with clinical metadata and whole-genome data for developing machine learning models to identify and predict patient factors driving toxicity response and sensitivity
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transport, health, energy, manufacturing, and smart cities. To be successful you will have: PhD in Computer Science, Data Science, Machine Learning, Electrical Engineering, or a related field with focus
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-compliance in ecological momentary assessment, or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models in small samples. The ideal candidate has prior
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machine learning frameworks. Proficiency in writing clean, efficient, and well-documented code. Mathematics skills including linear algebra and partial differential equations. Ability to implement software