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ICS Postdoctoral Fellowship in Prague, Czech Republic

Conditions

  • General conditions:
  • Each fellowship is of 12–24 months duration (with possible extension up to 36 months to be decided after the first year).
  • Application deadlines: June 30, 2020.
  • Starting date: August 1, 2020 or upon agreement.
  • Full-time fixed term contract appointment. Part time contract possible if taking care of a child.
  • Monthly gross salary: about 30 000-50 000 CZK based on qualifications and experience. Cost Of Living Comparison
  • Travel package for the total duration: up to 50 000 CZK for conferences and research stays.
  • Reallocation package for fellows coming from abroad: 10 000 CZK plus 10 000 CZK for family (spouse and/or children).
  • Willingness to apply for external funding is an advantage.
  • No teaching duties
  • Applicants must:
  • Have obtained a PhD during the last 3 years prior to the starting date (which must me before December 31, 2020), time spent on parental leave excluded.
  • Be fluent in English.
  • The applications are to be sent to ics@cs.cas.cz and should contain:
  • Curriculum Vitae.
  • Brief description of applicant’s research interests and of intended research plan during the fellowship highlighting possible cooperation inside the institute.
  • Three letters of recommendation – at most one from the Institute of Computer Science and at most one from the applicant’s current affiliation. The referees should send their recommendations directly to ics@cs.cas.cz.
  • A proof of the obtained degree.
  • For further information and informal enquiries concerning the position please contact hlinka@cs.cas.cz.
CountryCzech Republic
LabPrague
Starts on01/08/2020
Duration/Period12–24 months duration (with possible extension up to 36 months to be decided after the first year)
Deadline30/06/2020 23:59
Linkhttp://www.cs.cas.cz/job-offer/postdoctoral-fellowship/en
FilesICSfellowship2020_color.pdf
Keywordscomplex networks; brain dynamics; causality; information theory; time series; machine learning; neuroimaging; graph theory;

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