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understanding and generation, media forensics, anomaly detection, multimodal learning with an emphasis on vision-language models, computer vision applications for space. Key responsabilities: Shape research
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from different fields: AI (machine learning, big database, etc) Semiconductors
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hereafter. You can read more about career paths at DTU here . Further information Further information may be obtained from Morten Nielsen, morni@dtu.dk and at Immunoinformatics and Machine Learning (IML
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, and machine learning. The environment at GBI will allow researchers to undertake ambitious, long-term, collaborative research, and we will actively support the translation of research to commercial
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, transformer-based models), including experience with their application to biomedical and biological data; Experience with machine learning frameworks and programming languages (e.g. Python) for handling large
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computational biology/chemistry, machine-learning for biological or chemical data, metabolism, and drug discovery/design. Mentorship is taken seriously and every effort will be made to ensure the candidate is
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“big data” allowing agnostic and dynamic collection of information, to deliver a new class of research that will enable a better understanding of the clinical, molecular, behavioural and environmental
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methodologies: optogenetics, calcium imaging, viral tracing, tissue clearing, murine behavioral phenotyping, machine-learning behavioral analysis Familiarity with programming languages (e.g. R, Python) and an
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-of-the-art, large-scale discrete/combinatorial problems. Detailed information about the group can be found on the PCOG website . Your profile Required qualifications and experience: PhD in any discipline
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Geosciences, Environmental sciences, Civil or Environmental Engineering, Physics or Mathematics or a related discipline Experience in programming (e.g., Python, MATLAB, or similar), interest in machine learning