The Max Planck Institute for Empirical Aesthetics (MPIEA) in Frankfurt am Main, Germany, investigates neural mechanisms of skilled performance, perception, cognition, and emotional processing using music and other performing arts as models.
The Department of Cognitive Neuropsychology invites applications for a
Dr. Johanna Rimmele and Prof. Dr. Fredrik Ullén to complete a doctoral thesis on the topic “neural processes underlying rhythmic motor timing in speech and song”.
Language and music are fundamental aspects of our lives – with impairment resulting in serious derogation. While we understand spoken language or follow music seemingly effortlessly, the underlying cognitive computations and neural mechanisms are far from understood. Music can facilitate speech production, perception, and memory in healthy individuals and those with neurological disorders. Singing is a special case of music as it matches speech in terms of vocal production and verbal content, while the spectro-temporal characteristics are different. In this specific project, we investigate the neural mechanisms of speech and song processing, in particular the role of rhythmic motor timing. We use electrophysiological and neuroimaging methods, such as magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), as well as computational modeling.
The Department of Cognitive Neuropsychology at the MPIEA, headed by Prof. Dr. Fredrik Ullén, uses music as a model to analyze the brain mechanisms underlying human expertise, skill learning, and creativity. For more information about the department, please visit our website.
This position requires a master's degree in cognitive neuroscience, psychology, computational neuroscience, or a related field, as well as strong oral and written English skills. The ideal candidate for this position will have a strong interest in cognition, auditory processing, and acoustics. A strong background in statistics, experimental methods is required, as well as critical thinking skills and an eagerness to learn new techniques, tools, and methods. Previous experience with (and high motivation to explore) MEG or EEG, machine learning-based analysis techniques, as well as programming in, e.g., R, Python, and MATLAB is highly desirable.
The research will be conducted at the MPIEA with access to a CTF magnetoencephalography, a Siemens 3T MRI scanner (and from 2024 a 7T MRI scanner), and laboratories for behavioral and physiological experiments. The facilities are supported by an experienced staff of IT specialists and physicists. Analysis is performed on the institute's high-performance computing (HPC) cluster. The institute is a highly interdisciplinary and international scientific environment, with English and German being the languages spoken in the laboratory. It is located in an attractive area with excellent infrastructure in Frankfurt's Westend. You can expect a modern workplace with a pleasant and inspiring working atmosphere.
The position will start as soon as possible after February 1, 2024, for a fixed term of three years. The agreed working time is currently 39 hours per week. The salary is based on the Collective Agreement for the Public Service (TVöD Bund E 13, 65%) and is supplemented by an annual bonus. Further information can be found at mpg.de/doctoral_students.
The Max Planck Society strives for gender equality and diversity. We are also committed to increasing the number of people with disabilities in our workforce. Candidates from all backgrounds are therefore welcome.
Your application should include: your detailed CV, a cover letter explaining why you are interest in the research and in pursuing a PhD, and how your skills and abilities are suited to both, copies of relevant degrees and/or certificates, a brief (one-page) summary of your master's thesis, and the names and contact information of two references who have given their permission to be contacted.
Please submit these materials through our application management system no later than December 15, 2023.
If you have any questions about the project, please feel free to contact Dr. Johanna Rimmele or Prof. Fredrik Ullén via johanna.rimmele@ae.mpg.de.
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