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Field
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to function, and this process is tightly regulated by a network of chaperone proteins. At the heart of this network is Hsp90, a molecular chaperone essential for the folding and maturation of at least 20% of
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important question to solve, as DNA damage-stalled RNA polymerase causes bigger problems for the cells than the actual DNA damage itself. In this project we will use innovative single molecule imaging
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18 Sep 2025 Job Information Organisation/Company FEUP Department Human Resources Division Research Field Engineering » Other Engineering » Biomedical engineering Engineering » Computer engineering
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. Machines must be equipped in-situ with smart sensors and supported by systems that can process such as images and time series, in real time. Machine learning and AI have become essential for driving
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transfer. We use complementary approaches including cryo-EM, biophysical methods and in vivo functional assays to study the protein machineries involved in this process. Join our young, ambitious, and
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the opportunity to contribute to collaborative efforts at the interface of data science, imaging, and materials research. You will strengthen the data science and machine learning activities of the IAS-9 with
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industrial application. It is part of activities in ARCNL’s Source Department. The research activities of the Source Department and its EUV Plasma Processes group aim at the atomic- and molecular-level
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adipose tissue. In particular, we will study the role of different membrane receptors and their signaling pathways in the browning process. The various techniques used will include cell biology and genetic
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experiments as well as bioinformatics and advanced imaging techniques. Your core tasks are: Cloning and expressing recombinant proteins. Developing and optimizing purification protocols. Designing and
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of the identified structures via stereolithographic, 3D printing and textile techniques like tufting, machine-based embroidery techniques or non-interlaced 3D pre-forming. Development of advanced imaging and