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Post Doctoral Researcher in Human-Centered AI for Software Engineering, Department of Electrical ...
. The research to be addressed AI has been applied to Software Engineering for some time, and in areas such as software effort estimation, defect prediction, and project management in general. And more recently
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project RECLESS (Recycling versus loss in the marine nitrogen cycle: controls, feedbacks, and the impact of expanding low oxygen regions). RECLESS aims to predict how ongoing ocean deoxygenation impacts
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, and to develop predictive models that can guide the rational design of next-generation BioAg products tailored for diverse agricultural systems around the world. Responsibilities The postdoc position
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to protein engineering and molecular cloning, Experienced in bioinformatic genome analysis and computational tools related to protein structure analysis and prediction, Sufficient expertise in standard
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potential for exploiting temperature gradients for producing electricity and predict their long-term performance under real operating conditions. The project also includes modeling of heat transfer and
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to protein engineering and molecular cloning, Experienced in bioinformatic genome analysis and computational tools related to protein structure analysis and prediction, Sufficient expertise in standard
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and transport of proteins and lipids between cytosol and cilia by an unknown gating mechanism. By employing an integrative approach involving protein structure prediction by AlphaFold 3 combined with
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factors that predict the magnitude and spatiotemporal dynamics of applause behavior. The postdoc will also be expected to participate actively, constructively and respectfully in the academic life of CoMPS
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, protocols, and data standards across collaborating institutions and scales. This collaboration will support the generation of coherent, high-quality datasets and enable the development of predictive models
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motivated Postdoc candidate within the field of Immunoinformatics and prediction of T cell immunogenicity. HLA class II antigen presentation form the cornerstone of T-helper cell immunogenicity. Over the last