Postdoc in computational neuroscience / Understanding the dynamics of the neuronal activity encoding a realistic learning

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BEMÆRK: Ansøgningsfristen er overskredet

Are you interested in computational neuroscience and can you contribute to the development of the project understanding the dynamics of the neuronal activity encoding a realistic learning? Then the Department of Department of Molecular Biology & Genetics invites you to apply for a 2-year postdoc position.
 

Expected start date and duration of employment

This is a 2–year position from 1st of September 2023.


Job description


  • You will be working primarily on the analysis and modelling of large-scale and high-dimensional neuronal data to examine the dynamics of neuronal networks in the freely moving animal’s brain during learning and memory formation tasks.
  • The position will focus on computational modeling and analysis of the data acquired with single-unit large-scale calcium imaging in freely moving mice.
  • These activities will be in close collaboration with physiologists, neuroscientists, and behaviorists.



Your profile


Applicants should hold a PhD in computational neuroscience, electrical engineering, computer science, or similar.
  • Applicants should have a strong background in statistical analysis, signal processing, machine learning and data modeling.
  • Applicants must have sufficient background and familiarity with brain physiology, neuroscience and neuron function. Publications in the field of neuroscience and brain signal processing is preferred.
  • Applicants must have good skills and experience in programming with at least one of the following languages: Python, MATLAB or R.
  • Since people in the post-doc position have the possibility to teach, the candidate should preferably have university teaching experience in the relevant fields.
  • Since the work environment is very communicative, the person should have the ability to work in a group, mutual understanding of group members.
  • Applicants must have a good level of skills in English (reading, writing, speaking).
Finally, applicants must self-motivated and good in problem solving and can work independently.
 

Who we are

DANDRITE was established in 2013 as the Danish Node of the Nordic EMBL Partnership in Molecular Medicine, which was made possible thanks to a generous grant from Lundbeckfonden and Aarhus Universitet. DANDRITE is hosted by Aarhus University, where DANDRITE is organizationally placed in two departments: the Department of Biomedicine (Faculty of Health) and the Department of Molecular Biology and Genetics (Faculty of Natural Sciences).
 The Nabavi group is focusing on how plasticity at the synaptic and circuit levels in the brain relates to behavioral plasticity (learning and memory formation) and how the newly formed memories are integrated into the existing network (cellular and systems consolidation) using rodents as model organism.


What we offer


  • a well-developed research infrastructure, laboratories and access to shared equipment
  • an exciting interdisciplinary environment with many national, international and industrial collaborators
  • a research climate encouraging lively, open and critical discussion within and across different fields of research
  • a work environment with close working relationships, networking and social activities
  • a workplace characterised by professionalism, equality and a healthy work-life balance.



Place of work and area of employment


The place of work is Ole Worms Allé 4, 8000 Aarhus C, and the area of employment is Aarhus University with related departments. 
 

Contact information

For further information, please contact: Associate Professor, Sadegh Nabavi, +4593508246, snabavi@dandrite.au.dk. 

Deadline

Applications must be received no later than 28 June 2023.


Application procedure

Shortlisting is used. This means that after the deadline for applications – and with the assistance from the assessment committee chairman, and the appointment committee if necessary, – the head of department selects the candidates to be evaluated. All applicants will be notified whether or not their applications have been sent to an expert assessment committee for evaluation. The selected applicants will be informed about the composition of the committee, and each applicant is given the opportunity to comment on the part of the assessment that concerns him/her self. Once the recruitment process is completed a final letter of rejection is sent to the deselected applicants.


Letter of reference


If you want a referee to upload a letter of reference on your behalf, please state the referee’s contact information when you submit your application. We strongly recommend that you make an agreement with the person in question before you enter the referee’s contact information, and that you ensure that the referee has enough time to write the letter of reference before the application deadline. Unfortunately, it is not possible to ensure that letters of reference received after the application deadline will be taken into consideration.


Formalities and salary range


Natural Sciences refers to the Ministerial Order on the Appointment of Academic Staff at Danish Universities under the Danish Ministry of Science, Technology and Innovation.

The application must be in English and include a curriculum vitae, degree certificate, a complete list of publications, a statement of future research plans and information about research activities, teaching portfolio and verified information on previous teaching experience (if any). Guidelines for applicants can be found here.

Appointment shall be in accordance with the collective labour agreement between the Danish Ministry of Taxation and the Danish Confederation of Professional Associations. Further information on qualification requirements and job content may be found in the Memorandum on Job Structure for Academic Staff at Danish Universities.

Salary depends on seniority as agreed between the Danish Ministry of Taxation and the Confederation of Professional Associations.

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants.

Research activities will be evaluated in relation to actual research time. Thus, we encourage applicants to specify periods of leave without research activities, in order to be able to subtract these periods from the span of the scientific career during the evaluation of scientific productivity.

Aarhus University offers a broad variety of services for international researchers and accompanying families, including relocation service and career counselling to expat partners. Read more here. Please find more information about entering and working in Denmark here.

Aarhus University also offers a Junior Researcher Development Programme targeted at career development for postdocs at AU. You can read more about it here.

The application must be submitted via Aarhus University’s recruitment system, which can be accessed under the job advertisement on Aarhus University's website.
 


Aarhus University

Aarhus University is an academically diverse and research-intensive university with a strong commitment to high-quality research and education and the development of society nationally and globally. The university offers an inspiring research and teaching environment to its 38,000 students (FTEs) and 8,300 employees, and has an annual revenues of EUR 935 million. Learn more at www.international.au.dk/

INFORMATIONER OM STILLINGEN:

- Arbejdspladsen ligger i:

Aarhus Kommune

-Virksomheden tilbyder:

-Arbejdsgiver:

Aarhus Universitet, Universitetsbyen 81, 8000 Aarhus C

-Ansøgning:

Ansøgningsfrist: 28-06-2023; - ansøgningsfristen er overskredet

Ved skriftlig henvendelse: https://AU.emply.net/recruitment/vacancyApply.aspx?publishingId=04f9ff97-9d28-4080-a5cf-94e515472f50

Se mere her: https://job.jobnet.dk/CV/FindWork/Details/5848530

Denne artikel er skrevet af Emilie Bjergegaard og data er automatisk hentet fra eksterne kilder, herunder JobNet.
Kilde: JobNet