Postdoctoral Researcher in Computational Neuroscience: Effects of Neuromodulation on Learning in SRNNs

Updated: 4 months ago
Deadline: 11 Feb 2024

23 Dec 2023
Job Information
Organisation/Company

Radboud University
Research Field

Physics
Researcher Profile

Recognised Researcher (R2)
Country

Netherlands
Application Deadline

11 Feb 2024 - 23:00 (UTC)
Type of Contract

Temporary
Job Status

Not Applicable
Hours Per Week

40.0
Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

We are looking for a postdoctoral researcher to study the effects of neuromodulators in biologically realistic networks and learning tasks in the Vidi project 'Top-down neuromodulation and bottom-up network computation, a computational study'. You will use cellular and behavioural data gathered by our department over the previous five years on dopamine, acetylcholine and serotonin in mouse barrel cortex, to bridge the gap between single cell, network and behavioural effects.

The aim of this project is to explain the effects of neuromodulation on task performance in biologically realistic spiking recurrent neural networks (SRNNs). You will use biologically realistic learning frameworks, such as force learning, to study how network structure influences task performance. You will use existing open source data to train a SRNN on a pole detection task (for rodents using their whiskers) and incorporate realistic network properties of the (barrel) cortex based on our lab's measurements . Next, you will incorporate the cellular effects of dopamine, acetylcholine and serotonin that we have measured (see this paper and this preprint ) into the network, and investigate their effects on task performance. In particular, you will research the effects of biologically realistic network properties (balance between excitation and inhibition and the resulting chaotic activity, non-linear neuronal input-output relations, patterns in connectivity, Dale's law) and incorporate known neuron and network effects. You will build on the single cell data, network models and analysis methods available in our group, and your results will be incorporated into our group’s further research to develop and validate efficient coding models of (somatosensory) perception. We are therefore looking for a team player who can collaborate well with the other group members, and is willing to both learn from them and share their knowledge.


Requirements
Specific Requirements
  • You hold a PhD in computational neuroscience, mathematics, physics, computer science, AI or a similar computational field.
  • You have experience in working with machine learning models in (computational) neuroscience and are able to perform network simulations, analytical derivations and advanced data analysis.
  • You are a highly motivated, independent, critical and creative researcher who wants to bridge the gap between real data and abstract theoretical models.
  • You are a team player, ready to collaborate in a diverse multidisciplinary research group.
  • You have an excellent command of spoken and written English.
  • You have experience in coding (Python and/or Matlab).

Additional Information
Benefits
  • It concerns an employment for 0.8 - 1.0 FTE.
  • The gross monthly salary amounts to a minimum of €3,226 and a maximum of €5,090 based on a 38-hour working week, depending on previous education and number of years of relevant work experience (salary scale 10 ).
  • You will receive 8% holiday allowance and 8.3% end-of-year bonus.
  • You will be employed on the basis of a temporary contract for 26 months.
  • You will be able to use our Dual Career and Family Care Services . Our Dual Career and Family Care Officer can assist you with family-related support, help your partner or spouse prepare for the local labour market, provide customized support in their search for employment and help your family settle in Nijmegen.
  • Working for us means getting extra days off. In case of full-time employment, you can choose between 30 or 41 days of annual leave instead of the legally allotted 20.

Work and science require good employment practices. This is reflected in Radboud University's primary and secondary employment conditions . You can make arrangements for the best possible work-life balance with flexible working hours, various leave arrangements and working from home. You are also able to compose part of your employment conditions yourself, for example, exchange income for extra leave days and receive a reimbursement for your sports subscription. And of course, we offer a good pension plan. You are given plenty of room and responsibility to develop your talents and realise your ambitions. Therefore, we provide various training and development schemes.


Selection process

You can apply until 11 February 2024, exclusively using the button below. Kindly address your application to Fleur Zeldenrust. Please fill in the application form and attach the following documents:

  • A letter of motivation (max 2 pages).
  • Your CV including a publication list and the contact details of two academic referees.
  • A copy of a first-authored publication.

The first round of interviews will take place on Monday 11 March. The second round of interviews will take place on Monday 18 March.

You would preferably begin employment on 1 April 2024.
We can imagine you're curious about our application procedure . It offers a rough outline of what you can expect during the application process, how we handle your personal data and how we deal with internal and external candidates. If you wish to apply for a non-scientific position with a non-EU nationality, please take notice of the following information .


Additional comments

For questions about the position, please contact Fleur Zeldenrust, Hiring PI and Associate Professor, at [email protected] .


Website for additional job details

https://www.academictransfer.com/336197/

Work Location(s)
Number of offers available
1
Company/Institute
Radboud University
Country
Netherlands
City
Nijmegen
Postal Code
6525 XZ
Street
Houtlaan 4
Geofield


Where to apply
Website

https://www.academictransfer.com/en/336197/postdoctoral-researcher-in-computati…

Contact
City

Nijmegen
Website

http://www.ru.nl/
Street

Houtlaan 4
Postal Code

6525 XZ

STATUS: EXPIRED

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