Assistant Professor of Computational neuroscience at Department of Neuroscience

We are looking for a highly motivated and dynamic assistant professor who has worked with computational neuroscience and neuroengineering for a two year position with the Berg Laboratory to commence 15 January, 2026.

In this position, the assistant professor will analyze data on spinal neuronal population activity acquired using Neuropixels electrodes in awake, behaving animals. The job entails developing models of spinal motor function, primarily based on neuronal network modelling using rate-based neurons. We work as a team, and the person is expected to collaborate with the rest of the group.

Information on the department can be found at: Department of Neuroscience and the Berg lab web site can be found here: BERG LAB and information about the group leader, Rune Berg can be found here: Rune Berg

Our research
The research focus of the Berg lab has been to combine quantitative approaches of mathematics and physics with experiments using electrophysiology, genetics, tissue clearing and other biological tools to better understand the nervous system especially the motor system. 

The Berg group emphasized strong quantitative approaches in neuroscience. In particular, we believe investigating populations of neurons, networks, as opposed to the single-neuron tradition, is crucial. In turn, this will likely spur therapeutic strategies for individuals with neurological conditions, especially spinal cord injuries. Our key research areas are:

• Neuronal Population activity in the spinal cord and brain using large array electrophysiology, primarily Neuropixels probes.
• Development of novel probe technology in collaboration with neuroengineers.
• Network architecture in motor circuits.
• Histological clearing techniques for large sample imaging for network reconstruction
• In vivo, awake electrophysiology with chronic  electrodes and optical fibers implantation in the central nervous system.     

Your job
Position Overview: We are seeking a motivated and collaborative Assistant Professor to join our interdisciplinary research team. The successful candidate will focus on analyzing and modeling spinal neuronal population activity to advance our understanding of spinal motor function. This role is ideal for someone with a strong background in computational neuroscience, electrophysiology, and network modeling, who thrives in a team-oriented research environment.

Key Responsibilities:

1. Data Analysis:

• Lead the analysis of large-scale neuronal population activity data acquired using Neuropixels electrodes in awake, behaving animals.
• Apply advanced statistical and computational techniques to extract meaningful patterns and insights from complex neural datasets.
• Develop and implement algorithms for preprocessing, spike sorting, and decoding neural signals.

2. Computational Modeling:

• Design and develop rate-based neuronal network models to simulate spinal motor function.
• Use computational tools (e.g., Python, MATLAB, NEURON, or Brian2) to create biologically plausible models of spinal circuits.
• Validate models by comparing simulation results with experimental data.

3. Collaboration and Teamwork:

• Work closely with experimental neuroscientists, engineers, and other team members to integrate theoretical and experimental approaches.
• Contribute to collaborative projects by sharing expertise in data analysis, modeling, and interpretation.
• Participate in regular team meetings, journal clubs, and scientific discussions to foster a collaborative research environment.

4. Research and Publication:

• Lead and contribute to high-impact research projects aimed at understanding the neural mechanisms underlying spinal motor control.
• Publish findings in peer-reviewed journals and present results at national and international conferences.
• Seek external funding opportunities (e.g., grants, fellowships) to support and expand research initiatives.

5. Mentorship and Teaching:

• Mentor graduate and undergraduate students, providing guidance on research projects and technical skills.
• Assist in developing educational materials and contribute to teaching courses in computational neuroscience or related fields.

Qualifications and Skills:

Required:

• Ph.D. in Neuroscience, Computational Neuroscience, Biomedical Engineering, or a related field.
• Strong background in computational modeling of neural systems, particularly rate-based neuronal networks.
• Experience with electrophysiological data analysis, preferably using Neuropixels or similar high-density recording systems.
• Proficiency in programming languages such as Python, MATLAB, or R, and familiarity with data analysis libraries (e.g., NumPy, SciPy, Pandas).
• Demonstrated ability to work collaboratively in a team setting and communicate complex ideas effectively.
• Comprehensive knowledge of spinal cord anatomy, physiology, and motor control.

Preferred:

• Postdoctoral experience in computational neuroscience or a related field.
• Experience with machine learning techniques for neural data analysis.
• Track record of publications in high-impact journals and successful grant applications.

 

Work Environment:

• This position is part of a dynamic, interdisciplinary research group focused on understanding neural circuits and motor function.
• The candidate will have access to state-of-the-art computational resources, experimental facilities, and collaborative opportunities with leading researchers in the field.
• The role offers a balance of independent research and team-based projects, with professional growth and development opportunities.

Place of employment
The place of employment is at the Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen. We offer creative and stimulating working conditions in a dynamic and international research environment. Our research facilities include modern laboratories and core facilities.

Terms of employment
The average weekly working hours are 37 hours per week.

The position is a fixed-term position limited to a period of two years. The start date is 15 January 2026. Salary, pension and other conditions of employment are set in accordance with the Agreement between the Ministry of Taxation and AC (Danish Confederation of Professional Associations) or other relevant organisation. Currently, the monthly salary starts at 40,000 DKK/approx. 6,200 EUR (April 2025 level). Depending on qualifications, a supplement may be negotiated. The employer will pay an additional 18.07 % to your pension fund.

Foreign and Danish applicants may be eligible for tax reductions if they hold a PhD degree and have not lived in Denmark the last 10 years.

The position is covered by the Job Structure for Academic Staff at Universities 2024.

Questions
For further information please get in touch with Rune Berg on runeb@sund.ku.dk ; www.sund.ku.dk

Foreign applicants may find this helpful link: www.ism.ku.dk (International Staff Mobility).

Application procedure
Your application must be submitted in English by clicking ‘Apply now’ below. Furthermore, your application must include the following documents/attachments – all in PDF format:

1. Motivated letter of application (Max. one page)
2. CV incl. education, work/research experience, language skills and other skills relevant for the position
3. A certified/signed copy of a) PhD certificate and b) Master of Science certificate. If the PhD is not completed, a written statement from the supervisor will do.
4. List of publications
5. Teaching portfolio (If applicable)

 

Deadline for applications: 7 November 2025, 23.59pm CET

We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.

The further process
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the hiring committee. All applicants are then immediately notified whether their application has been passed for assessment by an unbiased assessor. Once the assessment work has been completed each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself.

You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/

The applicant will be assessed according to the Ministerial Order no. 242 of 13 March 2012 on the Appointment of Academic Staff at Universities.

 

Interviews are expected to be held in week 46

The University of Copenhagen wish to reflect the diversity of society and encourage all qualified candidates to apply regardless of personal background.