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Job Llhurmu6cdmf0i

PhDApplications Closed

Shervin Safavi

Unknown Organization
Dresden, Germany
Apply by Nov 1, 2023

Application deadline

Nov 1, 2023

Job location

Job location

Shervin Safavi

Geocoding

Dresden, Germany

Geocoding is still running and results will appear soon.

Source: legacy

Quick Information

Application Deadline

Nov 1, 2023

Start Date

Flexible

Education Required

See description

Experience Level

Not specified

Job location

Job location

Shervin Safavi

Geocoding

Dresden, Germany

Geocoding is still running and results will appear soon.

Source: legacy

World Wide map

Job Description

Please check

https://shervinsafavi.github.io/cmclab/join/bne_phd_202310/

for more details.

If you are interested, please submit your application (preferably) via TU Dresden’s Medical Faculty application portal (https://www.uniklinikum-dresden.de/de/jobs-und-karriere/stellenangebote/wissenschaft/phd-position-m-f-x/@@jetzt-mitarbeiter-werden) by November 30, 2023, otherwise via email. As required by the official announcement of the PhD position (https://www.uniklinikum-dresden.de/de/jobs-und-karriere/stellenangebote/wissenschaft/phd-position-m-f-x), for applying, please include, a cover letter, brief research interests, and your CV. Please do not hesitate to contact us for questions. If you're sending your application or contacting us (applications@cmclab.org) for questions, please use the subject heading of bne_phd_202310.

Requirements

  • Suggested skills (N=necessary
  • D=desired
  • P=plus)
  • (N) Have background (Master/Diploma) in (computational) neuroscience
  • neuroscience
  • physics
  • mathematics
  • statistics
  • machine learning
  • psychology
  • and other related fields.
  • (N) Being comfortable with programming (best would be
  • Python
  • or Matlab).
  • (D) Have experience in the analysis of neurophysiology data.
  • (D) Have experience with computational and systems neuroscience.
  • (D) Familiarity with machine learning techniques or/and sufficient mathematical background.
  • (P) Basic knowledge of software engineering (e.g.
  • packaging scientific tools).
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