3-year Ph.D. project, funded by la Caixa Foundation fellowship. Theme: Computational and neural bases of bilingualism. Goal: develop a model of bilingual development in the complementary learning systems framework. Direct link to position: https://finder.lacaixafellowships.org/finder?position=4739 Detailed Description: We seek a Ph.D. student with strong background (and masters) in a relevant domain (a cognitive, biological, or engineering field) and some experience with programming, data science, or computational modeling. The successful candidate will be involved in developing and computational models and/or running behavioral and neuroimaging studies, collecting and analyzing data, and disseminating the results in scientific conferences (presentations/posters) and peer-reviewed journals. The selected candidate will develop advanced technical and analytical skills and will have the opportunity to develop original experiments under the supervisors’ guidance. Applicants should demonstrate a keen interest in the key areas of cognitive neuroscience that are relevant for the research, coupled with strong computational skills (e.g., Python, Matlab, R). Experience with neuroscience techniques (e.g., MEG, EEG, MRI) and with analysis of neuroimaging data is desirable but not essential. A committed motivation to learning computational modelling and advanced analysis tools is a must, as well as the ability to acquire new skills and knowledge, and to work both independently and as part of a multidisciplinary team. A good command of English (the working language of the BCBL) is required; knowledge of Spanish and/or Basque is an advantage but not required. The candidate will enrol as a PhD student at the University of the Basque Country (UPV/EHU) and is expected to complete the PhD programme within 36 months. Training in complementary skills will be provided during the fellowship, including communication and research dissemination, IT and programming skills, ethics and professional conduct. The BCBL also provides support with living and welfare issues.

This postdoctoral position offers an exciting opportunity to combine computational modeling, psychophysics, and EEG to study the computational mechanisms underlying flexible evidence integration in perceptual decision making.

Doctoral Position in Computational Neuroscience. Are you curious about how the human brain stores memories? Have you wondered how we manage to navigate through space? Our dynamic research group uses diverse computational modeling approaches, including biological neural networks, cognitive modeling, and machine learning/artificial intelligence, to study learning and memory. Currently, we are actively seeking a talented graduate student to join our team, someone who will expand our computational modeling framework Cobel-Spike and use it to study how spiking neural networks can learn to navigate. This position is 65% at TV-L E13, starts as soon as possible, and is funded for 3 years.