Postdoctoral Position in Computational and Cognitive Neuroscience: Flexible, Theory-Driven Research Program on Human Perception and Cognition We invite applications for a postdoctoral research position in our lab at Boston University, directed by Rob Reinhart (website: https://reinhartlab.org/). Our work focuses on the computational and neural mechanisms of human perception and cognition. This position is supported by fully flexible research resources, offering an unusually high degree of freedom to co-develop a research program that most excites the postdoc and draws deeply on their expertise, in close intellectual partnership with the PI. The lab is fundamentally a basic science training environment, oriented toward building representational computational accounts of cognition. Our central goal is not merely to describe behavior and its correlates, but to identify and test the internal representations and operations that constitute the cognitive phenotype, and to articulate the causal mechanisms by which these representations are implemented in neural systems. Research Approach Our work aims to integrate: (1) Causal perturbation of neural systems, including high-definition transcranial alternating current stimulation (HD-tACS) and temporal interference (TI) stimulation, to directly test mechanistic hypotheses. (2) Computational modeling across levels, including: Electric field models, Formal and normative models, Cognitive models, Neural spiking models and neural mass models. (3) Rich, theory-driven experimental design, using behavioral measures (e.g., psychophysics, eye movements) that feed directly into computational models, with behavior serving as a window into latent representational structure rather than an endpoint of interest. (4) Human neuroscience methods, including EEG and fMRI, integrated with perturbation and modeling. (5) Advanced machine learning and multivariate analysis, including representational similarity analysis (RSA), multivariate decoding and encoding models, pattern component modeling (PCM), cross-validated model comparison, dimensionality-reduction and manifold-learning methods, regularized and probabilistic models, and related techniques for interrogating representational geometry and latent structure in neural and behavioral data. Intellectual Environment The lab values theoretical clarity, mechanistic explanation, and close coupling between experiment and model. We are especially interested in candidates who think carefully about: (1) What representations are being computed? (2) What operations transform them? (3) How these computations are implemented neurally. (4) How causal perturbation constrains theory. The postdoc will have substantial latitude to shape the direction of their research, develop new paradigms or modeling approaches, and pursue questions that cut across cognition, computation, and neuroscience. Qualifications We welcome applicants from a broad range of academic backgrounds relevant to the study of cognition, including cognitive neuroscience, cognitive science, neuroscience, psychology, and linguistics. Applicants with strong theoretical and computational training from related fields such as physics, applied mathematics, or computer science who are motivated to translate this expertise to questions in cognitive neuroscience are also encouraged to apply. Ideal candidates will have: (1) a strong interest in computational and mechanistic explanations of cognition; (2) experience with at least one of the following: computational modeling, EEG/fMRI, brain stimulation, advanced data analysis, or experimental design; and (3) a desire for deep, theory-driven training. Training and Career Development This position is designed as a launchpad for independent academic research careers, with the goal of preparing scholars for tenure-track faculty positions at R01 universities. Training emphasizes intellectual ownership, methodological breadth, and rigorous theoretical foundations, with close mentorship paired with strong encouragement to develop a distinctive research identity. The Reinhart Laboratory is embedded within a highly interdisciplinary research environment at Boston University, with connections spanning human neuroscience, electrophysiology, and computational neuroscience across Psychology, Neuroscience, Biomedical Engineering, Computer Science, and Mathematics. Dr. Reinhart holds a secondary appointment in Biomedical Engineering and is an active member of multiple interdisciplinary research centers that support cross-field collaboration and independent research development. The lab is affiliated with the Center for Research in Sensory Communication and Emerging Neural Technology (CReSCNT) and the Center for Systems Neuroscience (CSN), which together foster collaborative, theory-driven research linking neural mechanisms to behavior, computational modeling, and technological innovation. Through these centers, trainees have access to a broad intellectual community at Boston University and across the greater Boston-area research ecosystem. Applicants should send a short cover letter, CV, and names of three references to rmgr@bu.edu.