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flow cytometry, qPCR, ELISA, confocal microscopy, immunofluorescence or multiplex cytokine analysis. Experience in the analysis and interpretation of complex biological data. Competence in statistical
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, bioelectrical signalling and fibrotic cell-state transition. More information on the project can be found here: https://marcfernandezyague.com The successful candidate will conduct experiments at the Queen Mary
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enrichment, and social strength. We welcome those who would contribute to the further diversification of our department. Applicants may find some helpful information: http://www.physics.lancs.ac.uk/jobs
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to the activities of the Machine Learning & Data Science research group, develop rigorous mathematical proofs for convergence and asymptotic analysis of deep learning models, methods and algorithms, and collaborate
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or jointly in accordance with the project deliverables and project/group/School/College research strategy. 2. Document research output including analysis and interpretation of all data, maintaining records
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approach. Further information about current and past research of the lab can be found on our webpage https://scan-psy.univie.ac.at/research/ Your future tasks: We are looking for a postdoc in environmental
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such as breakwaters by using computational tools developed in our research group. These tools are based on discrete element method and they have bee validated against experimental data. You will start your
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dimensions of AI screening tools for mental health risk; from research design, research ethics submission, data collection, analysis, and outputs About You You will have or to be close to completion of PhD
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, the Division has a strong complementary background on using local scale community data such as vegetation plot data (e.g. EVA, https://euroveg.org/eva-database and ReSurveyEurope, https://euroveg.org/resurvey
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member of a research group with responsibility for carrying out research on the visual properties and evolution of eyes in trilobites as part of a project titled “Windows to the past: functional evolution