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Field
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. Requirements: PhD completed less than 7 years ago in Computer Science or related areas; experience in machine learning and data science (supervised/unsupervised models, recommendation and evaluation/robustness
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year. You should have knowledge and experience in bridging quantum and classical machine learning, and be fluent in English, both written and spoken. Assesment criteria Qualifications that are considered
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and machine learning with Prof. Jason M. Klusowski (https://klusowski.princeton.edu). The position is for one year with the possibility of reappointment based on satisfactory performance and
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). - Familiarity with machine learning principles and generative/classification models (PyTorch Lightning, torch, scikit-learn, etc.), as well as data/model analysis methods (PCA, t-SNE, etc.). - Proficiency in
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Classification Title: PhD in Bioinformatics, Computational Biology, Biomedical Engineering, Data Science, or a related field. Classification Minimum Requirements: PhD in Bioinformatics
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
work. Qualifications PhD in computer science, computational biology, engineering, or related fields. Experience developing deep-learning tools for image processing, automatic monitoring of agricultural
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off. To access this tool and learn more about the total value of your benefits, please click on the following link: https://resources.uta.edu/hr/services/records/compensation-tools.php CBC Requirement
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the project RIBOTICS (RNA Origami Technology in Cell Systems) funded by an Advanced Grant from the European Research Council (ERC). The intended starting date is 01st September 2026 or as soon as possible
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System Modelling group at TUM (https://www.asg.ed.tum.de/esm/home/) and will be closely involved in the Schmidt Sciences project MountAInWater, coordinated by the Institute for Science and Technology
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disorder. This project investigates early neural markers of psychosis by integrating multimodal neuroimaging with genetic and transcriptomic data and applying machine-learning approaches to identify