Postdoc in selective visual attention and rhythmic sampling

This postdoctoral position focuses on advanced research in selective visual attention and rhythmic sampling, requiring a strong background in cognitive neuroscience, psychology, or related fields. Candidates should possess expertise in experimental design and data analysis related to visual attention mechanisms, including the ability to investigate temporal dynamics and neural oscillations underlying attentional processes. Proficiency in neuroimaging techniques such as EEG, MEG, or fMRI is likely essential, alongside skills in signal processing and statistical analysis using software tools like MATLAB, Python, or R. Experience with behavioral paradigms assessing visual attention and the ability to integrate multimodal data would be advantageous. The role demands a thorough understanding of attention theories and rhythmic sampling models, as well as the capacity to conduct independent research, contribute to scientific publications, and collaborate within interdisciplinary teams. Strong analytical skills, familiarity with programming for data acquisition and analysis, and a track record of peer-reviewed research in cognitive neuroscience or experimental psychology are expected. Excellent communication skills for presenting findings and writing manuscripts are also important. This position is suited for candidates holding a PhD in neuroscience, psychology, or a closely related discipline, with a demonstrated commitment to advancing knowledge in visual attention and temporal sampling mechanisms.