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Field
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expected to be fully in person. This position does not have any supervisory responsibilities. Qualifications include a PhD in psychology or a related field and previous experience working in a research
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control venues such as the IEEE Conference on Decision and Control and IEEE Control Systems Letters, and in top machine learning conferences such as NeurIPS, ICML or AAAI, is expected. Proficiency in MATLAB
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, mechanical and durability testing, and integration with advanced machine learning models. The postdoc will collaborate closely with CEBE’s parallel work packages. Experimental and analytical data generated in
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of Python programming and a deep learning framework, preferably PyTorch. Solid knowledge of image processing, inverse problems, and machine learning. Significant research experience, demonstrated by quality
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, Automotive, and Mechanical Engineering, and provides professional education nationally and internationally, supporting lifelong learning. M2 strives for close collaboration between academia, industry, and
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Experience with super-resolution ultrasound, US localization microscopy, photoacoustic imaging, elasticity imaging, pulse encoding, solving inverse problems, machine learning, AI, SolidWorks, 3D printing FLSA
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provides professional education nationally and internationally, supporting lifelong learning. M2 strives for close collaboration between academia, industry, and society, focusing strongly on practical
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, bioinformatics, aging biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and
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to reconstruct subsurface defects; Implement image/signal‑processing or machine‑learning pipelines for automated flaw characterisation; Collaborate with the Federal University of Rio de Janeiro, including short
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they are kept fully up to date with progress and difficulties in the research projects. It is essential that you hold a PhD/DPhil in a quantitative discipline (e.g. Statistics, Machine Learning, Biostatistics, AI