The University Hospital Bonn (UKB) is one of Germany’s leading university hospitals, combining top-level performance in medicine and research with excellence in teaching. Each year, more than half a million patients receive inpatient and outpatient care at the UKB. Around 3,500 students study medicine and dentistry here, and over 600 people are trained annually in healthcare professions. With approximately 9,900 employees, the UKB is the third-largest employer in the Bonn/Rhein-Sieg region. In the Focus hospital ranking, the UKB ranks first among university hospitals in North Rhine-Westphalia and second nationwide in terms of case mix index (case severity). In 2024, the UKB raised nearly €100 million in third-party funding for research, development, and teaching. The F.A.Z. Institute has named the UKB “Germany’s Training Champion” and “Germany’s Most Attractive Employer” for the fourth consecutive year.

The SinzLab (Prof. **Fabian Sinz**, University of Göttingen) and the research group “Circuit Mechanisms of Behavior” (Prof. **Tobias Rose** at the IEECR at the University Hospital Bonn) invite applications for a **full-time position (38,5 h/week)** as:
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**Postdoctoral Researcher (m/f/d)**
 
We are seeking a highly motivated postdoctoral researcher to join our teams to work on a project funded by the European Research Council (ERC). The candidate would be jointly supervised by Prof. Sinz (Göttingen) and Prof. Rose (Bonn) and focus on experimental aspects of neural recording in freely moving animals (performed in Bonn) and data-driven characterization of visual-motor tuning principles (performed in Göttingen).

**Project Description:**
 

The project aims to develop a computational framework to understand how motor behavior influences visual processing in freely behaving mice. The successful candidate will perform neural recordings (miniature two-photon) in freely moving mice and analyze how motor behavior affects visual processing across multiple brain areas using deep learning models.
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**Tasks:**
 
·         Conduct neural recordings from visual cortex areas in freely moving mice using miniature 2-photon microscopy (established)

·         Process and analyze high-dimensional neural and behavioral data

·         Characterize visual and motor tuning principles using data-driven approaches

·         Design and implement *in silico *task paradigms to test the behavioral benefits of motor signals

·         Co-supervise PhD students and collaborate with computational team members

·         Verify computational predictions with experimental tests  

**Requirements:**

·         PhD in Neuroscience, Biology, or related field

·         Experience with in vivo neural recording techniques, particularly in rodents

·         Strong background in visual neuroscience

·         Proficiency in data analysis and programming (Python preferred)

·         Excellent communication and teamwork skills

** Preferred Qualifications:**
 
·         Experience with experimental design in freely moving animals

·         Experience with miniature 2-photon microscopy or similar techniques

·         Knowledge of machine learning approaches for neural data analysis

·         Experience with behavioral paradigms in rodents

·         Familiarity with computational modeling of neural systems

**The Position**
 
·         5-year, full-time position on E13 100% salary. Level will be determined based on experience

·         Based primarily at the lab of Dr. Tobias Rose at the University of Bonn, Germany

·         Opportunity to work in an interdisciplinary team of experimentalists and computational neuroscientists

·         Access to state-of-the-art recording equipment and computational resources

**We offer:**
 

·         **Responsible and diverse: **A position with plenty of room for creativity and responsibility within a supportive and collegial team

·         **Family-friendly flexibility: **Flexible working time models, access to a place in our company daycare center, and programs supporting employees returning from parental leave

·         **Smart commuting: **Excellent connection to the SWB public transport network and the option of an interest-free loan for the purchase of an e-bike

·         **Supported development: **Individual training opportunities through courses, e-learning programs, and coaching sessions

·         **Structured onboarding: **A systematic introduction to your new role and team

·         **Healthy at work: **A wide range of health and wellness programs, plus free membership at the UKB fitness studio

·         **Employee benefits: **Access to discounted offers for employees (corporate benefits)
 
We are committed to diversity and equal opportunities. Our goal is to increase the proportion of women in areas where women are underrepresented and to particularly promote their careers. We therefore urge relevantly qualified women to apply. Applications are treated in accordance with the State Equal Opportunities Act. Applications from suitable people with proven severe disabilities and those of equal status are particularly welcome.
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**How to apply:**
 

Who to contact?                                [sinz@uni-goettingen.de](https://mailto:sinz@uni-goettingen.de) & [tobias.rose@ukbonn.de](mailto:tobias.rose@ukbonn.de)

Email subject:                                      Start with "[PostDoc]"

What to include?                                What Ph.D. degree do you (soon) hold?

Curriculum Vitae with publication list

Statement of motivation (max 500 words) outlining your personal interest in our research area.

Links to code you have written (e.g. github or bitbucket)

Known programming languages and experience

Names and emails of two references

Possible start date

Until 13.01.2026
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**Prof. Tobias Rose**

**Circuit Mechanisms of Behavior**

**Institute of Experimental Epileptology and Cognition Research, IEECR**

**Universitätsklinikum Bonn**

**Venusberg-Campus 1**

**53127 Bonn**

\*\*E-Mail: [tobias.rose@ukbonn.de](https://mailto:tobias.rose@ukbonn.de)
** **
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**Prof. Fabian Sinz**

**Neuronal Intelligence Group**

**Lehrstuhl für Maschinelles Lernen**

**Georg-August-Universität Göttingen**

**Goldschmidtstraße 1**

**37077 Göttingen**
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\*\*E-Mail: [sinz@uni-goettingen.de](https://mailto:sinz@uni-goettingen.de)