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Offer 259 out of 437 from 22/07/22, 10:13

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Tech­ni­sche Uni­ver­sität Ber­lin - Fakul­tät IV - Insti­tut für Soft­ware­tech­nik und Theo­re­ti­sche Infor­ma­tik / FG Neu­ro­tech­no­lo­gie

Research Assistant - salary grade E 13 TV-L Berliner Hochschulen - 1st qualification period
(PhD candidate)

part-time employment may be possible

Working field:

The Neurotechnology Group offers a position for a research associate at a pioneering interface of research and teaching in different scientific disciplines. The group brings together staff with backgrounds in computer science, mathematics, computational neuroscience, biophysics. Our research focuses on the development of algorithms for the analysis and classification of EEG data and the modelling of neurophysical processes. Our expertise includes classical machine learning, deep learning, Riemannian geometry, realistic neural networks, forward modelling of head volume conduction, inverse methods and algorithms.

You can expect:
  • a small, highly motivated and international team working together in a personal atmosphere,
  • the opportunity, integrated into a team, to develop new research tasks in the field of neurotechnology and algorithms,
  • a good equipment,
  • teaching tasks in a team, especially in the tutorial of the lecture Algorithms and Data Structures,
  • offering your own courses (e.g. seminars and practicals),
  • Presenting your research results at international conferences and publishing in scientific journals,
  • The doctorate (PhD) under the supervision of experienced scientists,
  • Cooperation with international research groups,
  • Co-design of future research projects.

Requirements:

  • Successfully completed scientific university degree (Master, Diploma or equivalent) in computer science, mathematics, computational neuroscience, biophysics or a related field.
  • Sound knowledge of computer science, especially with regard to algorithms required Experience in using versioning tools, e.g. Git.
  • Sound knowledge in one or more of the following areas is an advantage: data analysis of EEG signals, Riemannian geometry, algorithms / computational geometry.
  • The willingness and ability to work interdisciplinary in an international team is expected.
  • Preference will be given to applicants with knowledge of Java and extensive programming experience in data analysis with Python.
  • Experience in scientific work and an independent working style is an advantage.
  • Very good knowledge of written and spoken English; the German language (language in the Bachelor's programme) must be business fluent in spoken and written (level C2); the ability to teach in both German and English is a prerequisite.

How to apply:

Please send your application with the reference number and the usual documents only by email in a single PDF file to Prof. Dr. Blankertz at imke.weitkamp@tu-berlin.de

By submitting your application via email you consent to having your data electronically processed and saved. Please note that we do not provide a guaranty for the protection of your personal data when submitted as unprotected file. Please find our data protection notice acc. DSGVO (General Data Protection Regulation) at the TU staff department homepage: https://www.abt2-t.tu-berlin.de/menue/themen_a_z/datenschutzerklaerung/ or quick access 214041.

To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities.

Technische Universität Berlin - Die Präsidentin - Fakultät IV, Fachgebiet Neurotechnologie, Prof. Dr. Blankertz, Sekr. MAR 4-3, Marchstr. 23, 10587 Berlin