PhD position in the "Neural Information Processing Group" (Klaus Obermayer)

Field: Modelling Neural Dynamics and the effects of Transcranial Electrical Stimulation

To be filled: As soon as possible

Application due: November 9th, 2023

Reference Number: IV-673/23

Tenure: 5 years

Remuneration: E-13 TV-L, 100%


Participation in the projects of the our research group in the field of computational neuroscience on modelling neural dynamics and the effects of transcranial electrical stimulation; collaboration with theoretical and experimental / clinical research groups of the Collaborative Research Center 1315 „Mechanisms and Disturbances of Memory Consolidation" (, cf. project B03) and the Bernstein Center for Computational Neuroscience Berlin (; assistance in the maintenance of the computer infrastructure of the research group; teaching tutorials for introductory courses in programming and algorithms & architectures for non-CS students. For information about our research group see


Successfully completed university degree (Master, Diplom, or equivalent) in Computational Neuroscience, Computer Science, Electrical Engineering, Mathematics, Physics, or related fields; in-depth knowledge in dynamical systems, very good command of the German and English languages, the ability to teach in both German and English is required; very good programming skills and competences in the operating system UNIX; experience in modelling neural systems, teaching experience, and experience in server administration (UNIX) are desirable.



Prof. Dr. Klaus Obermayer

Please send your application with the usual documents exclusively by e-mail to Prof. Dr. Klaus Obermayer at, quoting the reference number.


PostDoc position @TU Berlin on Computational Cognitive Neuroscience of Language in collaboration with UC Berkeley

Research Assistant (PostDoc position)

Field: Computational Cognitive Neuroscience of Language

To be filled: as soon as possible

Application due: August 4, 2023

Reference number: IV-339/23

Tenure: until 30/06/27

Remuneration: TV_L 13, 100 % without teaching obligation


Working field:
Project coordination and independent research on machine learning methods and models for robust neurocognitive applications; developing a computational modeling framework of brain signals to understand how language is represented in the brain; modeling fMRI- and EEG-data using deep learning-based machine learning techniques ("large language models"); language related features will be extracted using computational linguistics and state-of-the-art Natural Language Processing tools.


Applicants must hold a successfully completed university degree (Master, Diplom or equivalent) and a PhD in computer science or related fields (Electrical Engineering, Computational Neuroscience, Computational Linguistics); very good knowledge in acquisition and analysis of fMRI data, machine learning and Natural Language Processing is required (experience with acquisition and analysis of EEG or MEG data is an advantage); very good programming skills, preferably in Python are required; experience in publishing scientific papers and writing grant proposals for multidisciplinary research topics is required; experience in supervising students is required; very good English and German skills, both written and spoken, are required.

How to apply:

Please send your application with the usual documents exclusively by e-mail to Prof. Dr. Fatma Deniz at, quoting the reference number.



Postdoc position in the Meisel Lab

Research Assistant (PostDoc position)

Field: Computational Neurology

To be filled: as soon as possible

Application due: Screening of applications has recently started and will continue until the position is filled

Reference number: not available at the moment

Tenure: 3 years

Remuneration: TVöD 13, 100 %


Working field:
The position is funded by the Federal Ministry of Education and Research Germany (BMBF) as part of a research consortium to develop secure low power medical edge computing. We are working with data from patients with epilepsy who received a minimally invasive EEG device beneath the scalp for the chronic recording (months) of brain signals during wake and sleep. The device also has the capability to stimulate the brain to prevent seizures. To help with the analysis of massive amounts of EEG data, we are looking to hire a passionate postdoc with desire to build classification and forecasting algorithms aiming at estimating the risk of seizures in advance.


  • Applicant should hold a doctoral degree in any engineering field, physics, or neuroscience and have published scientific literature as a first author.
  • Strong abilities in computer programming (e.g. Python).
  • Prior experience with machine learning methods, signal analysis and advanced data analysis techniques.
  • Strong interpersonal communication skills in English and good written English.

Preferred requirements:

  • Hands-on experience in human electrophysiology recordings is a significant advantage.
  • Experience with deep-learning, machine-learning or statistical model development.


  • Acquire domain knowledge in epileptology.
  • The project lies at the interface between machine learning and EEG data analysis.
  • The goal of the project is to develop machine learning algorithms to classify EEG and forecast seizures.

How to apply:

To apply, please send a one-page motivation letter dedicated to this specific project, your up-to-date CV, and contact information for 2-3 references, as well as any other relevant documents to the PD Dr. Christian Meisel (christian.meisel (at)