Explainable Machine Learning / Deep Learning in Clinical Neuroimaging and Translational Psychiatry
1) PostDoc position (starting date: autumn 2022, 4 years; 100 %) at Charité – Universitätsmedizin (Berlin, Germany)
At Charité – Universitätsmedizin Berlin and the Bernstein Center for Computational Neuroscience, we are looking for a motivated and highly qualified PostDoc for methods development at the intersection of explainable machine learning / deep learning and clinical neuroimaging / translational psychiatry. The position will be located in the research groups of Prof. Kerstin Ritter and Prof. John-Dylan Haynes at Charité Berlin. The main task will be to predict response to cognitive-behavioral psychotherapy in retrospective data and a prospective cohort of patients with internalizing disorders including depression and anxiety from a complex, multimodal data set comprising tabular data as well as imaging data (e.g., clinical data, smartphone data, EEG, structural and functional MRI data). An additional task will be to contribute to the organization and maintenance of the prospective cohort. This study will be one of several projects in the newly established Research Unit 5187 “Precision Psychotherapy” (headed by Prof. Ulrike Lüken).
Requirements for the Postdoc:
– Excellent master and PhD degree in relevant field (e.g. computer science, mathematics, physics, psychology, computational neuroscience or related).
– Excellent methodological skills (esp. machine learning, deep learning, explainable AI, medical image analysis)
– Excellent programming skills in python
– Excellent writing and communication skills (in English)
– Strong interest in neuroscientific and psychiatric research
2) PhD position (starting date: autumn 2022, 4 years; 75 %) at Charité – Universitätsmedizin (Berlin, Germany)
At Charité – Universitätsmedizin Berlin and the Bernstein Center for Computational Neuroscience, we are looking for a motivated and highly qualified PhD student for analyzing structural and functional MRI data in patients with internalizing disorders (e.g., depression and anxiety) using machine learning methods. An additional task will be the acquisition of fMRI data together with other PhD students in the newly established Research Unit 5187 “Precision Psychotherapy” (headed by Prof. Ulrike Lüken). The PhD student will be supervised by Prof. Kerstin Ritter, Prof. Ulrike Lüken and Prof. Norbert Kathmann.
Requirements for the PhD student:
– Excellent master in relevant field (e.g. computer science, mathematics, physics, psychology, computational neuroscience or related).
– Very good methodological skills (esp. machine learning, deep learning, statistics, neuroimaging)
– Very good programming skills in python
– Excellent writing and communication skills (in English and German)
– Strong interest in neuroscientific and psychiatric research
Please send your application (motivation+CV+references) in one pdf-file (in English or German) asap to:
Prof. Dr. rer. nat. Kerstin Ritter
Charité – Universitätsmedizin Berlin
Department of Psychiatry and Psychotherapy
Bernstein Center for Computational Neuroscience
Sauerbruchweg 4, Charitéplatz 1, 10117 Berlin
E-Mail: kerstin.ritter@charite.de
Webpage: https://psychiatrie-psychotherapie.charite.de/en/research/translation_and_neurotechnology/machine_learning/