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<b>Postdoc/PhD candidate (f/m/d): Deep Learning for Image Analysis
& Visualization</b><br>
[<a class="moz-txt-link-freetext" href="https://www.vrvis.at/ueber-uns/offene-stellen/deep-learning-for-image-analysis-and-visualization">https://www.vrvis.at/ueber-uns/offene-stellen/deep-learning-for-image-analysis-and-visualization</a>]<br>
<br>
VRVis, Austria’s largest research institute for Visual Computing, is
seeking a skilled and creative mind, who is keen on a combination of
cutting-edge research in Deep Learning Solutions for Image Analysis
and Visualization, to join our successful team of researchers. The
position is located within the Biomedical Image Informatics Group at
VRVis in Vienna, Austria, performing projects in the medical and
industrial sector. We undertake our research in close collaboration
with our company partners and the Computer Graphics Research Unit at
TU Wien, i.e. combining scientific and industrial environments into
a vibrant research ecosystem.<br>
<br>
<b>Your responsibilities</b><br>
<br>
- Aim at developing novel machine learning - especially deep
learning - based methods for image and data analytics and/or
rendering solutions, i.e. help optimize the visualization and
real-time analytics of time dependent 3D ultrasound data, on medical
image analytics and acceleration of radiological workflows, as well
as image analysis for manufacturing.<br>
<br>
- Work in close collaboration with our industry and academic
partners as you will be embedded in one of our ongoing research
projects depending on your scientific profile and qualification.<br>
<br>
- Enjoy working in an applied research environment, seeking both,
high quality academic publications and the development of
cutting-edge solutions for our industry partners working in
real-world settings.<br>
<br>
- Project management and acquisition tasks and/or supervision of
students, as well as presentation and publication of your research
results at scientific conferences and renowned journals could be
tasked to you.<br>
<br>
- Also, in case you do not yet own a PhD, there is the opportunity
to pursue a PhD at TU Wien or another of our partner universities.<br>
<br>
<b>What you will bring to the team</b><br>
<br>
- PhD or master’s degree in computer science, statistics, math, or
another technical field related to<br>
image analytics and machine learning, especially deep learning, with
relevant practical experience<br>
<br>
- Strong programming skills in Python and experience in C++;
additional coding skills are favorable<br>
<br>
- Proven project experience with current state-of-the-art machine
learning frameworks like TensorFlow or PyTorch<br>
<br>
- Ability to work in an international and diverse team as well as
independently<br>
<br>
- High level of independent problem solving and creative thinking,
coupled with a good team spirit<br>
<br>
- Excellent communication skills, preferably English and German<br>
<br>
<b>Nice to have</b><br>
<br>
- Familiarity with (medical) visualization, in particular volume
rendering, volume segmentation, graphics and shader programming, and
(medical) imaging in practical settings.<br>
<br>
<b>What we offer in return</b><br>
- Open-ended contract, up to 40 hours per week<br>
- Location: Vienna, Austria<br>
- Office easily accessible via public transport<br>
- Flexible working hours, home office possible<br>
- Well-equipped workplace<br>
- Supportive atmosphere in an inclusive team<br>
- Possibility to travel to international conferences like CVPR,
NeurIPS, Eurographics and/or IEEE VIS<br>
- Salary according to collective labor agreement,
IT-Kollektivvertrag, with overpay depending on qualification and
previous professional experience<br>
<br>
<b>Contact</b><br>
Please forward your application including your CV, motivational
letter, recommendation letters/references to<br>
Franziska Steyer-Beerman (HR) via <a class="moz-txt-link-abbreviated" href="mailto:fsb@vrvis.at">fsb@vrvis.at</a> by January 31, 2022
at the latest.<br>
<pre class="moz-signature" cols="0">--
Eduard Groeller <a class="moz-txt-link-freetext" href="mailto:groeller@cg.tuwien.ac.at">mailto:groeller@cg.tuwien.ac.at</a>
TU Wien <a class="moz-txt-link-freetext" href="http://www.cg.tuwien.ac.at/">http://www.cg.tuwien.ac.at/</a>
(DVR: 0005886)</pre>
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