444 evolution "https:" "https:" "https:" "https:" "https:" "Here We Are" positions in Belgium
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Where to apply Website https://jobs.vito.be/o/phd-position-coupling-electrochemical-nitration-and-redu
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diverse classes of inhibitory neurons are specified and integrated into brain circuits during development. Our work bridges developmental neurobiology, disease modeling, and systems neuroscience. To do
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synthetic biology context (check our website at https://csb-bioport.mystrikingly.com/ and www.csb.ugent.be ). You will conduct research on aquaglyceroporin engineering and on the FWO-WEAVE project “Study and
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Description Function We are looking for one highly motivated PhD candidate with a master's thesis in cell biology, molecular biology, neurosciences or genetics to join our research group in the Development
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application, please contact solliciteren@kuleuven.be . Where to apply Website https://www.kuleuven.be/personeel/jobsite/jobs/60637164?hl=en Requirements Research FieldJuridical sciencesEducation LevelMaster
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@kuleuven.be or Prof. dr. Frank Verbruggen, mail: frank.verbruggen@kuleuven.be.In case of problems with the online application, please contact solliciteren@kuleuven.be . Where to apply Website https
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, for the preparation of a doctorate, contains: The PhD student will be working on the development of novel spectroscopic sensors, in the framework of the FWO-funded research project on Functionally
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At least 50% of your assignment will be spent on academic research in preparation of a doctoral dissertation. The topic of your research will be the evolution and speciation in the plant family Annonaceae
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; support multi‑omics data integration and analysis across multiple research groups; and collaborate on the development and maintenance of computational pipelines for spatially resolved transcriptomics and
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Infrastructure? No Offer Description The PhD candidate will work on the development of advanced statistical and machine learning methods for time series prediction, with applications mainly in the field of traffic