About the position
The postdoctoral fellowship position is a temporary position where the main goal is to qualify for work in senior academic positions.
The focus of the group is the analysis of population neural data, developing and applying methods from statistics, machine learning and topological data analysis (TDA). We collaborate heavily with experimentalists with evolving projects that present interesting challenges in computational neuroscience, such as neuron ensemble identification, state space discovery, latent dynamics characterization and relation to animal behaviour and computational models, etc. These projects require the advancement of methods, beyond the state-of-the-art, as well as neuroscientific knowledge to properly develop the theory along with the experiments and findings. The ideal candidates will have a background in either statistical/machine learning or TDA- approaches for the analysis of population neural data, preferably from Neuropixel probes. Here is an example of this line of research: Gardner & Hermansen et al., Toroidal topology of population activity in grid cells. Nature 602, 123–128 (2022). The selected candidates will be involved in one or more such projects, but we also encourage new topics and independent thinking.
The selected candidates will be part of a research group focused on neural data science at the Department of Mathematics, currently comprising 1 postdoc, 5 PhD students, associate professor Benjamin Dunn and many joint members from other groups – in particular in close collaborations at the Kavli institute – with backgrounds in mathematics, statistics, computer science, statistical physics and neuroscience. We are also part of a much larger local community at NTNU that includes strong basic, computational and translational neuroscience as well as medicine, mathematics and related research fields.
One of the positions is funded internally and the other is through a collaborative project from the Norwegian Research Council on personalized rehabilitation of stroke patients evaluated with multimodal quantitative tools (PROTEQT).
The selected candidates will report to Benjamin Dunn concerning daily work, and to the Head of the Department of Mathematical Sciences in employee matters.
Duties of the position
- Advancement of statistical/machine learning and/or TDA methods
- Work with experimentalists from the experimental design stage, methods development, application and until completion of the project
- Discuss and contribute to the local scientific community
- Research work, in collaboration with other members of the group
- Dissemination of results
Required selection criteria
- You must have completed a Norwegian doctoral degree or corresponding foreign doctoral degree recognized as equivalent to a Norwegian PhD in mathematics or statistics. If you can document that the PhD thesis has been submitted, your application can be assessed even if you have not yet defended your dissertation. Documentation of the obtained doctoral degree must be presented before you can take up the position.
- Documented experience in method development in statistics, machine learning, statistical physics or topological data analysis
- Documented experience with the analysis of neural data, preferably large-scale electrophysiological or calcium data
- Good written and oral English
- Completed application including document (CV, diplomas, cover letter, references)
The appointment is to be made in accordance with Regulations on terms of employment for positions such as postdoctoral fellow, Ph.D Candidate, research assistant and specialist candidate.
Preferred selection criteria
- Norwegian language skills
- Experience with computational modelling or statistical physics.
Personal characteristics
The ideal candidate is
- Highly motivated/…….