Dear all,
We are readvertising our ad for a PhD position working with our team at
the Department of Psychiatry at the VU University Medical Center in
Amsterdam, The Netherlands on projectsemploying 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.
For details please see below and attached. Please liberally forward to
possibly interested candidates or people that might know suitable
candidates. Deadline for applications is December 1, 2014.
Best wishes,
Lianne Schmaal
--
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(a)gmail.com <mailto:lianschmaal@gmail.com>,
l.schmaal(a)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(a)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(a)ggzingeest.nl
<mailto:l.schmaal@ggzingeest.nl>
On 26 August 2014 15:21, lianne schmaal <lianschmaal(a)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(a)gmail.com <mailto:lianschmaal@gmail.com>,
l.schmaal(a)ggzingeest.nl <mailto:l.schmaal@ggzingeest.nl>