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degree or above in Biostatistics, Biomedical Sciences or related disciplines with at least 3 years’ post-qualification experience (preferably in clinical research, epidemiological data analysis of large
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of gene regulatory networks in various cell types. The research will leverage a large in-house dataset from iCAN, complemented by publicly available data. These efforts aim to uncover in more detail
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we invent it. If you're passionate about joining a community that challenges the
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convolutional neural networks (CNNs) and large language models (LLMs) to analyze retinal and corneal data including visual fields, fundus photographs, optical coherence tomography (OCT) images and genetics data
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invites applications for a research scientist position, who will work with Dr. Ahmed Aziz Ezzat at ISE to support a project of designing data-driven models for large-scale atomistic simulations used
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and calibration of reports from various sources. Collect and analyse large-scale cross-industry accident data using FRAM (Functional Resonance Analysis Method) within LLMs to identify human-, technical
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happens, and how it can be made better. This is a role for someone who’s excited to work with big, messy, real-world data — and who wants to do more than just build models. We’re looking for a researcher
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. Furthermore, we develop advanced scattering methods and machine learning tools for data analysis. For more information, see www.soft-matter.uni-tuebingen.de Qualification and skills Candidates should have good
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for data analysis and research. Machine Learning Skills: Experience with machine learning algorithms, transformers, or large language models to analyze genomic data. Computational Proficiency: Skilled in R
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to promote big tau splice variant and will test these in vivo. Follows up on some of the regulators of tau that we have identified to determine precise site of interaction, and potentially design an assay