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the Department of Computer Science at Aalto University in Finland. You will be joining a larger group of researchers working on similar topics. The department has a strong community on related topics: research
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& written communication skills and influencing/behaviour skills to build strong networks with internal and external stake-holders, record keeping and attention to detail, ability to contribute to the team
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of tomorrow and creating novel solutions to major global challenges. Our community is made up of 13 000 students, 400 professors and close to 4 500 other faculty and staff working on our dynamic campus in Espoo
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the growth and stability of individual filaments or organise multiple filaments into various bundled and branched networks. This role will focus on a family of actin-binding proteins that regulates the actin
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The post holder will develop computational models of learning processes in cortical networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity
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multiple filaments into various bundled and branched networks. This role will focus on a family of actin-binding proteins that regulates the actin cytoskeleton and links it to other intracellular components
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and online data collection is required. The role also demands strong organisational, time-management, and communication skills to support the day-to-day coordination of data collection activities
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of the academic community. The appointment will be made as Senior Research Officer and the rest of this campaign and associated paperwork will refer to the position by this title. Duties of the Role You will work
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of tomorrow and creating novel solutions to major global challenges. Our community is made up of 13 000 students, 400 professors and close to 4 500 other faculty and staff working on our dynamic campus in Espoo
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Interpersonal and communication skills with demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and