44 parallel-programming-"Multiple"-"Humboldt-Stiftung-Foundation" positions at ICN2 in Spain
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ICN2 PhD Programme Programme description: The ICN2 offers a competitive PhD Programme to talented students who wish to develop a research career at one of the top European institutions in the field
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. ICN2 offers also in-house specialized seminars, such as our Open Knowledge Program, and training in various transferable skills, such as technology transfer and intellectual property, among others
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to read Japanese. Experience in parallel scientific programming. Experience with High Throughput calculations. Other research and software engineering experience will be considered Availability to travel
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interfacing, thin-film technology and nanofabrication, growth and characterization techniques and neural data analysis. The research assistant will specialize in multiple facets of neural interfaces development
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experimentation that combines life sciences with nanoscale phenomena, supporting the cutting-edge research activities of multiple ICN2 groups. The successful candidate will be responsible for overseeing
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multiple Research Support Units and Facilities, staffed by highly skilled scientists and technicians whose diverse expertise adds substantial value to ICN2's research community. The division has experienced
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multiple Research Support Units and Facilities, staffed by highly skilled scientists and technicians whose diverse expertise adds substantial value to ICN2's research community. The division has experienced
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interfacing, thin-film technology and nanofabrication, growth and characterization techniques and neural data analysis. The research assistant will specialize in multiple facets of neural interfaces development
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communication skills with both internal and external teams. Ability to work under pressure and manage multiple tasks simultaneously. Proficiency in project management and budget tracking tools. English (high
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Synchrotron developing correlative (S)TEM in-situ experiments on catalysts, from SACs to multiple types of nanostructures. This position is linked to the AMADE PID2023 project funded by AEI / MCIN, led by Prof