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<span style="mso-ansi-language:EN-US" lang="EN-US">The Connectivity
Group (lead: Prof. Dr. Svenja Caspers) of the Institute of
Neuroscience and Medicine (INM-1), Research Centre Jülich
(Germany) is seeking applications for a</span>
<div class="moz-forward-container">
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US"> </span></p>
<p class="MsoNormal"><b><span style="mso-ansi-language:EN-US"
lang="EN-US">PostDoctoral Research Position in Population
Neuroimaging</span></b></p>
<b> </b>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US">(E 13 TVöD; 39 hours/week)</span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US"> </span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US">The Connectivity Group focuses on the
investigation of brain variability throughout the life span in
relation to environmental and genetic factors, with a
particular focus on the aging brain and taking advantage of
large population-based cohorts who underwent MR neuroimaging
(e.g. UK Biobank, German National Cohort, Human Connectome
Project, 1000BRAINS). Specific aspects include structural,
resting-state functional connectivity as well as advanced
diffusion imaging for structural connectivity analyses,
including graph-theory analyses. Large cohorts of thousands of
subjects are processed using adjusted pipelines and workflows
for high-throughput imaging analytics based on common software
packages (e.g. FreeSurfer, FSL, MRtrix) on available
high-performance computing systems of the Research Centre
Jülich. Current interests cover topics in advanced statistical
analyses and data-driven methods using machine-learning and
deep learning approaches. These efforts are part of current
projects within the Human Brain Project (HBP).</span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US"> </span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US">The successful candidate has a PhD in
neuroscience, computer science, psychology, medicine or
related fields and has experience with processing and analyses
of MR neuroimaging data in larger cohorts. A strong interest
and expertise in applying machine-learning to large
neuroimaging datasets is highly desired to enable the
candidate to conduct novel and innovative research projects to
understand the normal variability of brain aging.</span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US"> </span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US">Your profile:</span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US">- deep knowledge of several software packages for
processing of neuroimage data (e.g. FreeSurfer, FSL, MRtrix),
also including respective python packages (e.g. NiPy, DiPy)
and longitudinal pipelines</span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US">- profound expertise in multivariate statistical
analyses, including usage of software for large-scale
statistical analyses (e.g. R) and modelling of non-linear and
longitudinal effects</span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US">- profound programming skills (e.g. Python)
enabling high-throughput big data analyses</span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US">- knowledge of and interest in machine-learning
and deep-learning techniques to be applied to large neuroimage
datasets of population-based cohorts</span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US">- familiarity in working with large datasets</span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US">- strong publication track record</span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US">- ability to work independently</span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US">- high proficiency in English</span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US"> </span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US">The applicant will become part of an
interdisciplinary team of PostDocs, PhD and MD students with
various backgrounds. He / she will have ample possibilities to
expand his / her own knowledge and expertise and interact and
collaborate with colleagues from different fields, including
big data analytics, genetics, epidemiology and microscopic
analyses. With our group closely collaborating with the Jülich
Supercomputing Center, the applicant will join current efforts
in bringing population neuroimaging analytics to
high-performance computing clusters for efficient and novel
analyses approaches. The applicant will be involved in the
supervision and mentoring of PhD, MD, master and bachelor
students.</span></p>
<p class="MsoNormal"><span style="mso-ansi-language:EN-US"
lang="EN-US">Funding for the position is available for two
years. Applications will continue to be received until the
position is filled.</span></p>
<p><span
style="font-size:12.0pt;font-family:"Calibri",sans-serif;
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mso-bidi-theme-font:minor-bidi;mso-ansi-language:EN-US;mso-fareast-language:
EN-US;mso-bidi-language:AR-SA" lang="EN-US">Please send your
comprehensive application, including CV, publication record,
copies of relevant certificates and either reference letters
or names of two potential references to Prof. Dr. Svenja
Caspers (<a href="mailto:s.caspers@fz-juelich.de"
moz-do-not-send="true">s.caspers@fz-juelich.de</a>).</span>
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<div class="moz-signature">-- <br>
==============================<br>
<b><font size="2"> Univ.-Prof. Dr. med. Dr. rer. pol. Svenja
Caspers </font></b><font size="2"><br>
<br>
<font size="2"> Direktorin Institut für Anatomie I <br>
Heinrich-Heine-Universität Düsseldorf <br>
40221 Düsseldorf (Deutschland) <br>
Tel.: 0211-8112678 <br>
Email: <a class="moz-txt-link-abbreviated"
href="mailto:svenja.caspers@hhu.de" moz-do-not-send="true">svenja.caspers@hhu.de</a>
<br>
<a class="moz-txt-link-abbreviated"
href="mailto:svenja.caspers@med.uni-duesseldorf.de"
moz-do-not-send="true">svenja.caspers@med.uni-duesseldorf.de</a>
<br>
<br>
<i> und </i><br>
<br>
Arbeitsgruppe Konnektivität <br>
Institut für Neurowissenschaften und Medizin (INM-1) <br>
Forschungszentrum Jülich GmbH <br>
52425 Jülich (Deutschland) <br>
Tel.: 02461-611742 <br>
Email: <a class="moz-txt-link-abbreviated"
href="mailto:s.caspers@fz-juelich.de"
moz-do-not-send="true">s.caspers@fz-juelich.de</a> <br>
<br>
<br>
<br>
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