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Friedrich-Alexander-Universität Erlangen-Nürnberg

Friedrich-Alexander-Universität Erlangen-Nürnberg
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Ph.D. Student Position in Systems Neuroscience

Your workplace
Institute of Physiology and Pathophysiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)

Our benefits

  • Regular promotion to the next level and increase in salary pursuant to the collective bargaining agreement for the public service of the German Länder (TV-L) or remuneration pursuant to the Bavarian Public Servants Remuneration Act (BayBesG) plus an additional annual bonus
  • 30 days annual leave at five working days per week with additional free days on December 24 and 31
  • Flexible working hours and models and the possibility to take time off in lieu
  • Occupational pension scheme and asset accumulation savings scheme
  • Family-friendly environment with childcare options, also during school holidays
  • Working from home generally possible after training
  • A wide range of training courses and opportunities for professional development
  • Thorough onboarding process with a dedicated team
  • Joint team activities
  • Subsidized food and drinks in our student restaurants
  • Offices within comfortable walking distance of public transport
  • Active health management
  • IT-supported facility management system

Your Tasks
The laboratory of Prof. A. Ponomarenko is seeking a doctoral student with a strong interest in

the dynamics of neuronal circuits and behavior. A central research topic of our group is neural

coding and dynamics underpinning cognitive control of learned and instinctive (innate)

behaviors. Using in vivo electrophysiology, opto-, chemogenetics, and machine learning

approaches we have previously shown that network oscillations organize neuronal signaling

from the hippocampus, prefrontal cortex, and the lateral septum to and within the

hypothalamus, and crucially contribute to the regulation of locomotion (Bender et al., 2015),

food seeking (Carus-Cadavieco et al., 2017) and intake (Altafi et al., 2024), and behavioral

transitions (Chen et al., 2024).

Your Profile
You hold a Master’s (or equivalent) in neuroscience or a related field and are genuinely curious

about neuronal dynamics and behavior. Prior experience with in vivo techniques, including

animal behavior and computational data analysis, is highly beneficial. Motivation to acquire

computer coding skills is required. You bring a constructive, problem-solving mindset to the

project, are prepared for sustained and focused work, and value effective communication with

your team and supervisor.

Supplementary description
Hier gibts ergänzende Bemerkungen

Application deadline

2026-06-30

Title

Ph.D. Student Position in Systems Neuroscience

Job start date

2026-05-01

Payment

Working time

full time

Weekly working hours

40

### Temporary Contract yes

Reason for temporary contract

Project

Further general conditions

Location

Universitätsstrasse 1
91054 Erlangen

Contact

Prof. Alexey Ponomareko
Tel.: +49 9131 85-29302
Mobil:
alexey.ponomarenko@fau.de

Please apply via our online platform instead of sending applications by post or e-mail. Applications sent to us by post will not be returned.

With regard to the personal data collected during the application process, please refer to our information pursuant to Art. 13 and 14 of the General Data Protection Regulations at .

FAU is a modern, cosmopolitan and family-friendly employer. We welcome your application irrespective of your age, gender, cultural and social background, religion, ideological beliefs, disability or sexual identity. Applicants with a disability or who are considered to be equivalent to people with a disability will be given preference provided their aptitude, performance and capability are essentially the same. We are happy to offer part-time positions, provided a job-sharing arrangement means that the tasks in the area are fully covered.

If you wish, you may invite a person responsible for ensuring equal rights to accompany you to the job interview without incurring any disadvantages.