Postdoc in Connectomics Analysis ot the human brain

Vrije Universiteit Amsterdam
  • Postdoc in Connectomics Analysis ot the human brain
  • Postdoctoraal
Do you like to work with complex data? Do you like working with big data on the intersection of neuroscience, connectomics and genetics? Do you want to work in an ambitious research environment in the Center for Neurogenomics and Cognitive Research (CNCR)? Please keep reading and apply at Vrije Universiteit Amsterdam.

Location: AMSTERDAM
FTE: 0.8 - 1

Job description

The Dutch Connectome Lab (dutchconnectomelab.nl) at the Complex Trait Genetics Lab & Center for Neurogenomics and Cognitive Research in Amsterdam (see www.cncr.nl) is seeking applicants for a Postdoc position in cross-disorder connectome analysis of the human brain. The successful candidate will be part of a large ERC project in the group of PI Martijn van den Heuvel at the department of Complex Trait Genetics at the VU. The aim of the project is to gain insight into the transdiagnostic effects of the human brain connectome and the integration of this data with recent functional and structural connectome properties and recent genetic discoveries, utilizing large-scale bioinformatic databases and resources.

The human brain -our brain- is a large complex network of interconnected regions; the ‘connectome’. In the last decade advances in the field of connectomics have started to map and study the complex organization of brain networks, with the aim to get a better understanding of how brain connectivity plays a central role in brain function and disease disfunction. The field of disease connectomics has the specific aim to map and study how changes to the connectome may play a role in the etiology of a variety of brain conditions, ranging from individual symptomatology to neurological and psychiatric conditions. New technologies and data analysis techniques have enabled to map which systems and brain connections are involved in which disorders. A large open question is how brain systems may relate to each other across disorders and how we can best describe disease specific effects. A second large open question is how such potential cross-disorder and disorder-specific effects may relate to underlying common and unique genetic and molecular effects. To address these challenges, you will work on large-scale MRI and genetics databases and use (and develop) state-of-the-art methods on connectomics, genetics, and Machine Learning. You will work in a highly enthusiastic and motivated team of PhD students and PostDocs working on this project, with diverse backgrounds, including, bioinformatics, artificial intelligence, neuroimaging, computational neuroscience, psychology and genetics.

You have affinity with working with large datasets and have knowledge of MATLAB, Python, R, or other scientific coding/programming. Affinity with computational neuroscience, connectomics and/or Machine Learning is appreciated.

Your duties
  • perform connectome analysis on neuroimaging data
  • integrate connectome findings across datasets
  • supervise PhD students working on the project
  • work on developing new statistical methods to compare networks cross conditions
  • apply bioinformatic tools for integrating results from different biological resources
  • think critically
  • work with highly motivated and enthusiastic team members
  • actively take part in discussions and have frequent contact with CNCR neuroimaging, genetics and neuroscience labs
  • authoring and co-authoring manuscripts submitted to high quality journals
  • support (10% of time) to teaching
  • frequently present work at international communities (at conference calls or conferences)

Requirements

  • PhD/MSc in any of the of the following fields: Mathematics, Physics, Artificial Intelligence, (Computational) Neuroscience, Biology, Genetics and/or Statistics, Informatics (webdevelopment)
  • experience with neuroimaging techniques, preferably connectomics; bioinformatics; computational biology is highly appreciated
  • a good ability to write and read English
  • experience with Python or R language and some experience with scientific programming
  • support ‘open science’: share your tools and data with the wider scientific community. Sharing is caring

What are we offering?

A challenging position in a socially involved organization. On full-time basis the remuneration amounts to a minimum gross monthly salary of €2.846 (scale 10)
and a maximum €4,490 (scale 10), depending on your education and experience. The job profile: is based on the university job ranking system and is vacant for at least 0.8 FTE.

The initial employment contract will affect a period of 1 year.
Additionally, Vrije Universiteit Amsterdam offers excellent fringe benefits and various schemes and regulations to promote a good work/life balance, such as:
  • a maximum of 41 days of annual leave based on full-time employment
  • 8% holiday allowance and 8.3% end-of-year bonus
  • solid pension scheme (ABP)
  • optional model for designing a personalized benefits package

About Vrije Universiteit Amsterdam

The ambition of Vrije Universiteit Amsterdam is clear: to contribute to a better world through outstanding education and ground-breaking research. We strive to be a university where personal development and commitment to society play a leading role. A university where people from different disciplines and backgrounds collaborate to achieve innovations and to generate new knowledge. Our teaching and research encompass the entire spectrum of academic endeavor – from the humanities, the social sciences and the natural sciences through to the life sciences and the medical sciences.

Vrije Universiteit Amsterdam is home to more than 30,000 students. We employ over 5,500 individuals. The VU campus is easily accessible and located in the heart of Amsterdam’s Zuidas district, a truly inspiring environment for teaching and research.

Diversity
We are an inclusive university community. Diversity is one of our most important values. We believe that engaging in international activities and welcoming students and staff from a wide variety of backgrounds enhances the quality of our education and research. We are always looking for people who can enrich our world with their own unique perspectives and experiences.

The Faculty of Science
The Faculty of Science inspires researchers and students to find sustainable solutions for complex societal issues. From forest fires to big data, from obesity to medicines and from molecules to the moon: our teaching and research programmes cover the full spectrum of the natural sciences. We share knowledge and experience with leading research institutes and industries, both here in the Netherlands and abroad.

Working at the Faculty of Science means working with students, PhD candidates and researchers, all with a clear focus on their field and a broad view of the world. We employ more than 1,250 staff members, and we are home to more than 11,000 students.
 

About the department Complex Trait Genetics
Research at the department of Complex Trait Genetics focuses on identifying the genetic mechanisms of brain-related traits. We develop novel statistical and bioinformatics tools to optimally analyze large genome-wide data sets for complex traits, combine them with biological data and generate hypotheses that can be tested in functional studies to obtain mechanistic insight.
 

Application

You are requested to write a letter in which you describe your abilities and motivation, accompanied by your curriculum vitae, a list of grades of your MSc and the names and contact details of two scientific referees. Please compile all this together in one document and convert it to pdf.

Are you interested in this position? Please apply via the application button and upload your documents as mentioned above until 29/07/2022.

Applications received by e-mail will not be processed.

Vacancy questions
If you have any questions regarding this vacancy, you may contact:

Name: prof. dr. M.P. (Martijn) van den Heuvel
Position: Full Professor
E-mail: martijn.vanden.heuvel@vu.nl
Telephone: +31 20 59 833 43

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