Postdoc 'Develop statistical and machine learning tools for smartphone monitoring and neuroimaging data'
3 years We are looking for an excellent post-doctoral research associate to work on a European Research Council-funded project that aims to develop and apply advanced statistical and machine learning methods for the analysis of passive smartphone monitoring (‘digital phenotyping’) data. In addition, you link these data to measures of neurobiology derived from brain imaging (structural MRI, functional MRI and brain connectivity data).
The ultimate aim of this project is to integrate quantitative measures of biology and behaviour in order to predict illness trajectories in mood disorders (depression and bipolar disorder). This project is 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.
This project has a strong and analytical focus. You will be expected to develop machine learning techniques from basic principles, including both classical statistical and machine learning techniques (e.g. Bayesian and regularization-based methods) and deep learning technology (e.g. recurrent neural networks). The successful candidate will also be expected to produce software tools to enable other researchers to take advantage of the innovations produced in this project. In addition, the project will also involve curation and quality control of large digital phenotyping datasets plus elements of multi-modal data fusion.
An integral part of this international project is a two-year secondment to the University of Illinois in the USA to work with the developers of the BiAffect digital phenotyping platform (Assoc. Prof Alex Leow).
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 position is for 36 months, and should begin in 2021 or early in 2022.
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. We provide annual courses, both professional and personal.
In addition to your monthly salary and an annual vacation allowance of 8%, you will receive 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.
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.
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 a postdoc with a strong interest in biological or theoretical neuroscience, and an interest in clinical applications of machine learning. Prior experience with smartphone monitoring technology as well as experience with neuroimaging data analysis techniques and software (e.g. FSL, FreeSurfer, SPM) is desirable, but not essential. Prior hands-on experience in machine learning and AI-based techniques is vital. Other highly desirable characteristics include experience with similar sources of data.
In addition you possess the profile below:
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 the ability to work effectively in an interdisciplinary team.
Highly self-motivated, curious and enthusiastic about scientific research and will work with others in our lab and in the institute to solve problems and contribute to high-quality neuroscience investigations.
All additional information about the vacancy can be obtained from Dr. Andre Marquand, associate professor.Use the Apply button to submit your application.