Postdoc in Bayesian Methods and Transfer Learning in Cognitive Neuroscience

The Biological Psychology Lab at the Carl von Ossietzky University Oldenburg, within the School VI of Medicine and Health Sciences, is offering a postdoctoral position in Bayesian Methods and Transfer Learning in Cognitive Neuroscience. This DFG-funded project, led by Dr. Carsten Gießing, focuses on enhancing brain-behaviour predictions in small fMRI samples by leveraging knowledge from large neuroimaging datasets through Bayesian approaches and graph-theoretical models of brain connectivity. The research aims to advance methods for predicting attentional performance and drug effects in pharmacological fMRI studies, with applications in both basic and translational neuroscience. The successful candidate will be responsible for designing, programming, and implementing Bayesian analyses of fMRI connectivity and graph-theoretical brain network models. Additional tasks include developing and validating transfer learning methods and latent change score models, contributing to the creation of an open-source Python toolbox for brain connectivity, preparing scientific publications, and presenting research findings at international conferences. Collaboration with project partners, including Prof. Christiane Thiel (Psychopharmacology) and Prof. Andrea Hildebrandt (Statistical Modelling), is integral to the role. Applicants must hold a PhD in psychology, neuroscience, statistics, computer science, mathematics, physics, or a related field, and demonstrate proven expertise in statistical methods, multivariate statistics, and programming (preferably Python and/or R). A strong publication record and excellent English communication skills are required. Preferred qualifications include experience with neuroimaging data analysis (especially fMRI connectivity), Bayesian data analysis, and latent variable models. The University of Oldenburg offers a vibrant interdisciplinary research environment, access to state-of-the-art neuroimaging facilities (MRI, MEG), high-performance computing resources, and opportunities to collaborate on DFG-funded programmes such as META-REP and GRK Neuromodulation. The position is paid according to E13 TV-L collective bargaining law, with benefits including special annual payment, public service pension scheme, asset-related benefits, and 30 days annual leave. Flexible working hours and pro-rata mobile work options support a family-friendly environment. Female candidates and applicants with disabilities are strongly encouraged to apply and will be given preference in case of equal qualifications. The application deadline is 31 March 2026. For further information, contact Dr. Carsten Gießing at [email protected]. Applications should be sent as a single PDF (motivation letter, CV with publication list, degree certificates and transcripts, and contact details of two referees) to [email protected]. Additional job details can be found at https://uol.de/job973en .