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, an excellence-based research institute KU Leuven, one of Europe’s leading research universities State-of-the-art research facilities An extensive VIB and KU Leuven training program to broaden your
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computational and machine learning approaches, you will decipher genomic regulatory programs and infer the evolutionary patterns of gene regulatory networks in cortical neurons, study their developmental origin
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the capacity to independently plan and execute research with precision. A keen interest in nanobodies, drug delivery, and/or brain barriers is essential, accompanied by hands-on experience in molecular biology
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programming languages including bash scripting, MATLAB, C/C++, Golang, and Python Working knowledge of free5GC/OpenAirInterface/srsRAN open-source software stack. Practice in other open-source mobile network
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. Be sure to include the following attachments: a motivation letter your academic CV a concise research plan based on the project theme (max. 1500 words) The selection committee reviews all applications
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lab focuses on the characterization of plant signaling networks that steer plant specialized metabolism within tightly regulated fitness programs, in particular those modulated by stress hormones
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outreach events related to antenna design, channel modeling, FPGA's programming, and satellite communication, inspiring young generations to be interested in related topics. Design phased array design using
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to adapt to the research environments while being full members of two labs Desirable skills Experience with Spectral flow cytometry Experience with myeloid cells biology basic/intermediate programming
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dynamics of BLA to PFC connectivity and function; (2) identifying the molecular programs during critical developmental windows that influence BLA to PFC connectivity; (3) investigating the plasticity and
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
, or related fields Strong programming skills in Python, R, and experience with Linux environments Demonstrated experience in processing and analyzing large-scale genomic and transcriptomic datasets