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Careers - Open positions in the Brain and Data Science Lab

We welcome inquiries for MSc projects or lab rotations.

 

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Student Assistant Positions (80hrs / month)

The position is offered by the Technische Universität Berlin (TUB), FG Unsicherheit, inverse Modellierung und maschinelles Lernen (UNIML) with a maximum duration of 2 years.

The following tasks and responsibilities are envisioned -

  • Implementation of data analysis pipelines in Matlab and Python (30%)
  • Integration of research codes into open source toolboxes and plugins (30%)
  • Assistance in the acquisition and analysis of EEG and other data for scientific studies (30%)
  • Contribution to the group's publications (10%)

 

Requirements: The successful candidate should -

  • have good knowledge in computer science and mathematics
  • have solid programming skills in Matlab and Python, and have experience in software engineering
  • be fluent in English and German (written and spoken)
  • be motivated and a good team player
  • ideally, have experience in analyzing neurophysiological time series data, expertise in signal processing
  • optionally, have some experience with collecting EEG data from human participants

 

The Brain and Data Science Group at Charité 

We develop machine learning and signal processing methods for the analysis of non-invasive brain signals in health and disease. We are located at the Berlin Center for Advanced Neuroimaging (BCAN) on the beautiful historic Charité Campus Mitte (see picture) in the center of Berlin. The group is tightly linked with the Department of Uncertainty, Inverse Modeling and Machine Learning at Technische Universität Berlin, and Research Group 8.44 Machine learning and Uncertainty at Physikalisch-Technische Bundesanstalt (PTB) Berlin, both also led by Dr. Stefan Haufe. The group is currently supported by an ERC starting grant of the European Union, the German Science Foundation (DFG), and the Einstein Foundation Berlin. See braindata.charite.de for further information on our group.

 

Application 

Applicants should send a short introduction, a CV, proof of enrolment, and, if available, transcripts, to Ilaria Cicchetti-Nilsson (i.cicchetti-nilsson@tu-berlin.de).

 

Flyer

Please find the PDF flyer here