PhD student: MRI-based biomarkers for treatment stratification of depression
The research of the PhD candidate will mainly be dedicated to MRI and patient data analysis for extracting biomarkers indicating the risks for chronic …
- de Rondom, Eindhoven, Noord-Brabant
- Tijdelijk contract / Tijdelijke opdracht
- Uren per week:
- 38 uur
The research of the PhD candidate will mainly be dedicated to MRI and patient data analysis for extracting biomarkers indicating the risks for chronic depression development. Depression is the most prevalent neuropsychiatric disorder, and in 15-20% of cases becomes chronic. Currently, there is no objective metric to determine whether a patient with depression will have chronic depression or will recover quickly. Therefore the treatment and medication choice is often not optimal which leads to long and costly treatments.
The PhD project is aiming at discovering MRI-based biomarkers (indicators) to predict the course of disease and enable its management. We aim at a prospective study: scanning patients using multiple (f)MRI modalities soon after the diagnosis and twice later. Based on (f)MRI data analysis the prognosis of the disease outcome should be made. We will analyse functional MRI, including resting state and task-based scans, spectroscopy and other MRI modalities, which will be acquired by applying latest techniques such as multi-echo and multi-band approaches. This research is part of the Dutch national project Neurotrend in which the partners form a multidisciplinary team. The following partners are involved in Neurotrend: TU/e, Philips, Kempenhaeghe, GGZe. The PhD student will become part of the team and will collaborate with the other PhD candidate who is a medical doctor.
The main challenge in this study lies in identifying the most informative MRI acquisition modality and developing its analysis chain so that the treatment navigation of depression can be achieved. The candidate will apply the existing and create novel image analysis techniques to find the solution.
Signal Processing Systems group, Electrical Engineering, TU/e
The candidate will work in the Signal Processing Group (SPS) at the Department of Electrical Engineering in TU/e. The Signal Processing Systems group is conducting a broad range of signal and image analysis research for medical applications, digital communication and lighting systems. The impact of the work of the group is evident from a very close cooperation with industrial and clinical partners as well as with research institutes and from international recognition and awards of the team.
The ideal candidate should hold a MSc degree in computer science or electrical engineering with emphasis on signal processing, image/video processing, computer vision and good programming skills. Knowledge and skills related to MRI analysis are a plus.
ArbeidsvoorwaardenWe offer a challenging job in a dynamic and ambitious university through a fixed-term appointment for a period of 4 years. The research must be concluded with the attainment of a Ph.D. degree. As an employee of the university you will receive a competitive salary as well as excellent employment conditions. The salary starts at € 2325.-per month (gross) in the first year, increasing up to € 2972.- per month (gross) in the last year. Moreover, an 8% holiday allowance and 8,3% end-of-year allowance is provided annually. Assistance for finding accommodation can be given. The university offers an attractive package of fringe benefits such as excellent technical infrastructure, child care, savings schemes, and excellent sports facilities.
TU/e also offers you the opportunity for personal development by developing your social and communication skills. We do this by offering every PhD student a series of courses in the PROOF program as an excellent addition to your scientific education.
Additionele informatieAdditional Information
Additional information about the vacancy can be obtained from:
Dr. S. Zinger, e-mail address: s.zinger[at]tue.nl .
If you are interested in this position you can apply by using the 'Apply now'-button'. Please send us (only pdf files are accepted:)
Please keep in mind; you can upload only 5 documents up to 2 MB each