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PhD position: Closed loop control for deep brain stimulation

We have an open PhD position for developing closed-loop control systems for deep brain stimulation!

Deep brain stimulation (DBS) is an established therapy for Parkinson’s disease (PD). Currently, after electrode implantation, DBS parameters (for example, amplitude or frequency) are tuned by hand by an expert clinician. This infrequent tuning has been found  insufficient to adapt to fast changes in the disease progress or varying symptoms intensity due to e.g. medication.

These challenges call for research on closed-loop DBS systems that allow to adapt stimulation parameters in real time as a function of brain signals such as EEG, ECoG or LFPs. To this end, we seek to develop control systems (based for example in reinforcement learning) able to cope with complex non-stationary brain dynamics, which in the context of PD, are mainly caused by disease progress, stimulation, and medication.

We investigate such closed-loop approaches in collaboration with our partners at the University Medical Center Freiburg---where the implantation surgeries and inpatient visits take place---and with a company focussing on neural implant technology.

Do you want to know more? Find here the full description of the position

Postdoc Position at University Medical Center Freiburg

There is a Postdoc position available at the University Medical Center Freiburg in the context of a BCI motor rehabilitation study. While this position is at the University Medical Center, it will be in close cooperation with our lab. Please find the full offer below.

The Research Group “Neuroplasticity and Neuromodulation” is seeking a highly motivated, German-speaking Postdoctoral researcher for a DFG-funded joint project performed together with the Brain State Decoding Lab (Dr. Michael Tangermann, Institute of Informatics, The vacancy is for a period of 1 year with potential extension for 1 year.

We investigate strategies to enhance motor learning and limb function in patients with brain lesions, e.g. after stroke. We use a Brain-Computer Interface (BCI) to decode brain signals in close to real-time and use the decoded information for the online-adjustment of rehabilitative motor training within the training sessions. The applicant will primarily work with neurological patients. He/she will be mainly responsible for patient recruitment, neurological testings and EEG-based motor training, as well as analysis of behavioural, electrophysiological, EEG and MRI data. We expect the applicant to supervise research assistants and medical students, prepare data for scientific publications and assist in preparation of research grant applications.

Candidates with a MD degree or a PhD degree in neuroscience, (neuro)psychology, cognitive science, neuroinformatics and related areas are considered. German language skills are mandatory due to work with the patients. Practical experience in the design and execution of electrophysiological measurements (EEG, ECoG, MEG, EMG, LFP), ideally in the context of Closed-Loop BCI studies, is considered a distinct advantage. Applicants should demonstrate evidence of publications in international journals.

To apply please send a statement of your motivation and research interests, a complete CV and a publication list by email to and . The Albert Ludwigs University Freiburg is committed to equal opportunity. We strongly encourage applications from qualified women and persons with disabilities.

Student assistant wanted for machine learning tasks with Brain-Computer Interfaces

We are looking for a highly motivated student (preferably master-level) with a background in computer science and a high interest in brain-computer interfaces and machine learning!

HiWi für Patientenstudien mit Brain-Computer Interfaces

Gehst du freundlich und offen mit Menschen um? Bist du zuverlässig und zeitlich flexibel? Dann ist diese, die richtige HiWi Stelle für dich!