-- Lianne Schmaal, PhD Post-doctoral researcher GGZ inGeest/Department of Psychiatry VU University Medical Center P.O. Box 74077 1070 BB Amsterdam The Netherlands Tel: +31-207884592 email: lianschmaal@gmail.com mailto:lianschmaal@gmail.com, l.schmaal@ggzingeest.nl mailto:l.schmaal@ggzingeest.nl ----------------------------------------------------------- *The project* The focus of the proposed PhD project is two-fold; First, the PhD student will will employ advanced computational and statistical methods to evaluate the prognostic value of neuroimaging modalities, biomarker, genetic, environmental and clinical characteristics and their combination to classify the course of depression and anxiety. A second part of the project focuses on employing these methods to disentangle phenotypic heterogeneity of depression by identifying different subtypes based on a rich set of neuroimaging and clinical data and biological protein information, and by exploring the genetic basis of different subtypes and their association with course of depression and treatment response. For these purposes, you will work with data from the Netherlands Study of Depression and Anxiety (www.nesda.nl http://www.nesda.nl) in which an extensive battery of detailed longitudinal clinical, biomarker, neuroimaging and genetic data have been collected in a large cohort. You will also work with similar data from other international cohorts, and with data from the MOTAR study (www.motar.nl http://www.motar.nl) in which the effects of antidepressant and running treatments are examined. This project will integrate across these data-sources using a variety of methods, including the application of supervised and unsupervised machine learning techniques. You will be involved in the processing of neuroimaging data (structural MRI, functional MRI), associating these data with biomarker, clinical and genetics information and using machine learning methods to classify the patients. You will be working in a multidisciplinary team with young and enthusiastic researchers, who have expertise in psychiatry, genetics, neuroimaging, statistics/engineering and epidemiology. ** *Your challenge * As a PhD Student your main tasks and responsibilites are: * Help examine predictors of the naturalistic course and treatment response in depression and anxiety; * Identifying subtypes of depression and anxiety based on multimodal data sources; * Apply unsupervised and supervised machine learning methods, such as Support Vector Machine and/or probabilistic methods, to genetic, multi-modal neuroimaging, clinical and environmental data from the NESDA study, the MOTAR study and other international cohorts; * Write various scientific papers on the above topics, and complete your research with a PhD thesis. ** *Your profile* We are looking for a highly motivated and enthusiastic researcher with a strong interest in psychopathology who has the following background and experience: * A strong numerate background (i.e. a Master's degree in computer science, mathematics, (medical) informatics or technology, engineering, medical image analysis or related discipline), preferably with emphasis on machine learning, pattern classification, and/or multivariate image analysis; * Experience with neuroimage analysis or with (bio) statistics is desirable; * You have excellent statistical and strong computer programming skills (good command of LINUX, scripting, and Matlab); * You have excellent communications skills in English, both written and verbal; * Having experience in writing (international) publication(s) is a plus. ** *Benefits* Salary Scale: OIO (EUR 2.200 in the first year that increases to EUR 2.818 gross per month in the fourth year, based on 36 hours per week). We also offer a set 8.3% end-of-year bonus and 8% holiday pay. For more information about our fringe benefits, please visit http://www.werkenbijvumc.nl/vumc/arbeidsvoorwaarden/ (Dutch version). The PhD position is for four years, you will start with a contract for 12 months. ** *Additional information* The Department of Psychiatry of the VU University Medical Center (VUMC) and GGZ inGeest collaborately conduct research, education and academic patient care. The main focus is on depression and anxiety disorders, two common psychiatric disorders with high public health impact. Psychiatric research is embedded in two VU research institutes: EMGO+ and Neuroscience Campus Amsterdam. In this research area more than 150 persons from different disciplines (e.g. psychiatry, psychology, health science) collaborate. ** *Interested?* For more information about position or the application procedure you can contact Dr. Lianne Schmaal, via telephone number: +31(0)20 – 788 4592 or email: l.schmaal@ggzingeest.nl mailto:l.schmaal@ggzingeest.nl. Please submit your candidacy by latest December 1, 2014 by emailing your CV and motivation letter to Dr. Lianne Schmaal: l.schmaal@ggzingeest.nl mailto:l.schmaal@ggzingeest.nl On 26 August 2014 15:21, lianne schmaal <lianschmaal@gmail.com mailto:lianschmaal@gmail.com> wrote: Dear all, We are seeking talented candidates for a PhD position working with our team at the Department of Psychiatry at the VU University Medical Center in Amsterdam, The Netherlands. For details please see below. Please liberally forward to possibly interested candidates. Deadline for applications is September 7, 2014. Best wishes, Lianne Schmaal ----------------------------------------------------------- *The project* The focus of the proposed PhD project is two-fold; First, the PhD student will will employ advanced computational and statistical methods to evaluate the prognostic value of neuroimaging modalities, biomarker, genetic, environmental and clinical characteristics and their combination to classify the course of depression and anxiety. A second part of the project focuses on employing these methods to disentangle phenotypic heterogeneity of depression by identifying different subtypes based on a rich set of neuroimaging and clinical data and biological protein information, and by exploring the genetic basis of different subtypes and their association with course of depression and treatment response. For these purposes, you will work with data from the Netherlands Study of Depression and Anxiety (_www.nesda.nl_ http://www.nesda.nl) in which an extensive battery of detailed longitudinal clinical, biomarker, neuroimaging and genetic data have been collected in a large cohort. You will also work with similar data from other international cohorts, and with data from the MOTAR study (_www.motar.nl_ http://www.motar.nl) in which the effects of antidepressant and running treatments are examined. This project will integrate across these data-sources using a variety of methods, including the application of supervised and unsupervised machine learning techniques. You will be involved in the processing of neuroimaging data (structural MRI, functional MRI), associating these data with biomarker, clinical and genetics information and using machine learning methods to classify the patients. You will be working in a multidisciplinary team with young and enthusiastic researchers, who have expertise in psychiatry, genetics, neuroimaging, statistics/engineering and epidemiology. *Your challenge * As a PhD Student your main tasks and responsibilites are: • Help examine predictors of the naturalistic course and treatment response in depression and anxiety; • Identifying subtypes of depression and anxiety based on multimodal data sources; • Apply unsupervised and supervised machine learning methods, such as Support Vector Machine and/or probabilistic methods, to genetic, multi-modal neuroimaging, clinical and environmental data from the NESDA study, the MOTAR study and other international cohorts; • Write various scientific papers on the above topics, and complete your research with a PhD thesis. *Your profile* We are looking for a highly motivated and enthusiastic researcher with a strong interest in psychopathology who has the following background and experience: • A strong numerate background (i.e. a Master's degree in computer science, mathematics, engineering, medical image analysis or related discipline), preferably with emphasis on machine learning, pattern classification, and/or multivariate image analysis; • Experience with neuroimage analysis or with (bio) statistics is desirable; • You have excellent statistical and strong computer programming skills (good command of LINUX, scripting, and Matlab); • You have excellent communications skills in English, both written and verbal; • Having experience in writing (international) publication(s) is a plus. *Benefits* Salary Scale: OIO (EUR 2.200 in the first year that increases to EUR 2.818 gross per month in the fourth year, based on 36 hours per week). We also offer a set 8.3% end-of-year bonus and 8% holiday pay. For more information about our fringe benefits, please visit _http://www.werkenbijvumc.nl/vumc/arbeidsvoorwaarden/_ (Dutch version). The PhD position is for four years, you will start with a contract for 12 months. *Additional information* The Department of Psychiatry of the VU University Medical Center (VUMC) and GGZ inGeest collaborately conduct research, education and academic patient care. The main focus is on depression and anxiety disorders, two common psychiatric disorders with high public health impact. Psychiatric research is embedded in two VU research institutes: EMGO+ and Neuroscience Campus Amsterdam. In this research area more than 150 persons from different disciplines (e.g. psychiatry, psychology, health science) collaborate. *Interested?* For more information you can contact dr. Lianne Schmaal, via telephone number: +31(0)20 – 788 4592 tel:%2B31%280%2920%20%E2%80%93%20788%204592. For more information about the application procedure you can contact mr. Wessel Haytink, recruiter, via telephone number: +31(0)6 – 1066 7718. Please submit your candidacy by latest *September 7, 2014* with reference number D2.2014.00077WH via the following link: _http://bit.ly/PhDMachineLearning_ ----------------------------------------------------------- -- Lianne Schmaal, PhD GGZ inGeest/Department of Psychiatry VU University Medical Center P.O. Box 74077 1070 BB Amsterdam The Netherlands Tel: +31-207884592 tel:%2B31-207884592 email: lianschmaal@gmail.com mailto:lianschmaal@gmail.com, l.schmaal@ggzingeest.nl mailto:l.schmaal@ggzingeest.nl