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genome encodes gene expression levels. You will undertake large scale data generation from primary human samples using a method recently pioneered by the host laboratory (Hua et al., Nature 2021 https
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, biodiversity monitoring, and climate resilience. The work supports strategic priorities in Environmental Sciences, Software/Cyber. PhD researchers will explore how AI-driven Earth observation, computer vision
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Adaptive Learning in Brain-Robot Interactions School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications accepted all year
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field. Have proven expertise in statistical modelling and machine learning for large and complex datasets. Have proficiency in Python and/or R for time-series and sensor data analysis. Have an interest in
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of Informatics. You will be part of Visual Intelligence and the DSB group. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/293458/phd-research-fellow-in-deep-learning
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
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at: www.fz-juelich.de/gp/Careers_Docs Further information on doctoral degrees at Forschungszentrum Jülich (including its various branch offices) is available at https://www.fz-juelich.de/en/careers/phd We
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. The project will provide the student with extensive training in large-scale data integration, machine-learning methods, field-based environmental monitoring and eDNA analysis, as well as experience working
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computational biology/chemistry, machine-learning for biological or chemical data, and drug discovery/design. Mentorship is taken seriously and every effort will be made to ensure the candidate is able to achieve
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application! We are looking for a research engineer within the Division of Statistics and Machine Learning (STIMA) at the Department of Computer and Information Science. In this position, you will have the