Postdoc 'Development statistical and machine learning tools...
We have multiple vacancies (up to five) for excellent post-doctoral research associates to work on various projects focusing on the development and application of advanced statistical and machine learning methods for the analysis of clinical neuroimaging data and other types of data (e.g. measurements derived from smartphone monitoring and satellite-based measures of the environment). We are looking forward to meet you!
The projects are hosted by the Donders Institute for Brain, Cognition and Behavior at the Radboud University Medical Center (Cognitive Neuroscience department) under the supervision of
Assoc. Prof. Andre Marquand and Prof. Christian Beckmann and integrated into the wider academic research environment at the Donders Institute.
At a high level, the focus of these projects is to develop novel statistical and pattern recognition approaches for analyzing magnetic resonance imaging (MRI) data (structural MRI, functional MRI, connectivity) in the first instance in addition to smartphone-based digital phenotyping data (providing quantitative measurements of behaviour) and satellite monitoring data (providing measures of the environment). Many of the projects also have a focus on applications to mental health disorders (e.g. depression, bipolar disorder, autism).
You will develop and apply a range of techniques, spanning both classical statistical approaches (e.g. classical and Bayesian analysis methods) and machine learning methods (e.g. kernel methods, matrix factorization techniques, supervised/unsupervised and deep learning). You will also produce software tools to enable other researchers to take advantage of the innovations produced in these projects.
Tasks and responsibilities
Discuss, plan and perform research in a stimulating environment.
Develop statistical approaches for data analysis from fundamental principles.
Apply these statistical models to large-scale population cohorts.
Publish findings in peer-reviewed journals and present at international scientific conferences.
Produce software tools to enable for the use of the wider scientific community.
Assist with the supervision of students and more junior staff.
Work in an interdisciplinary team of international scientists.
The positions are for 36-48 months, and should begin in 2022 or early 2023. Working at Radboud university medical center means that you are ahead of the curve and working together on the healthcare of the future. And there is more. Our secondary terms of employment are impressive. These are fully tailored to you thanks to our Employment Conditions Selection Model. At Radboud university medical center, you will be given trust, and you will take the responsibility to handle everything together.
A gross monthly salary between € 3.047 and € 4.800 (scale 10) based on full-time employment.
An annual vacation allowance of 8% and an end-of-year bonus of 8.3%.
If you work irregular hours, you will receive an allowance.
As a full-time employee (36 hours per week), you are entitled to approximately 168 vacation hours (over 23 days) per year.
Radboud university medical center pays 70% of the pension premium. You pay the rest of the premium with your gross salary.
You get a discount on health insurance as well: you can take advantage of two group health insurance plans. UMC Zorgverzekering and CZ collectief.
We provide annual courses, both professional and personal.
In addition to our terms of employment, we also offer employees various other attractive facilities, such as childcare and sports facilities. Want to learn more? Take a look at the CAO UMC. The Donders Institute for Brain, Cognition and Behaviour is a world leading centre for cognitive neuroscience and offers a unique, multidisciplinary working and learning environment with opportunities for developing expertise in a diversity of research areas and techniques. The centre is equipped with three MRI scanners (3 x 3T) and access to a high field (7T) MR system plus a 275-channel MEG system, an EEG-TMS laboratory, several (MR-compatible) EEG systems, and high-performance computational facilities.
Radboudumc Radboud university medical center is a university medical center for patient care, scientific research, and education in Nijmegen. Radboud university medical center strives to be at the forefront of shaping the healthcare of the future. We do this in a person-centered and innovative way, and in close collaboration with our network. We want to have a significant impact on healthcare. We want to improve with each passing day, continuously working towards better healthcare, research, and education. And gaining a better understanding of how diseases arise and how we can prevent, treat, and cure them, day in and day out. This way, every patient always receives the best healthcare, now and in the future. Because that is why we do what we do.
Read more about our strategy and what working at Radboud university medical center means. Our colleagues would be happy to tell you about it.
#weareradboudumc We are looking for highly self-motivated candidates who are curious and enthusiastic about scientific research and who will work with others in our lab and in the institute to solve problems and contribute to high-quality neuroscience investigations. The projects are all highly interdisciplinary and integrate machine learning and statistics with cognitive neuroimaging and clinical neuroscience. Therefore, a keen interest in cognitive or clinical neuroscience is highly desirable.
Furthermore it is
essential that you have:
Completion of doctoral degree in a numerate discipline such as statistics, computer science, engineering, cognitive neuroscience / psychology or other relevant field of study.
Highly proficient in programming in languages such as Python, R, Matlab or C++.
A strong academic track-record, including publications in international journals.
A proactive attitude, good written and oral communication skills, and be able to work effectively in an interdisciplinary team.
And it is
desirable that you have:
Experience with neuroimaging data analysis techniques and software (e.g. FSL, FreeSurfer, SPM).
A strong interest in biological or theoretical neuroscience.
An interest in clinical applications of machine learning.
Prior experience with smartphone or satellite monitoring technology.
Any questions? Please contact Dr. Andre Marquand, Associate Professor or Prof. Christian Beckmann, Full Professor. Use the Apply button to submit your application.