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text-decoration-thickness: initial; text-decoration-style:
initial; text-decoration-color: initial; background-color:
rgb(255, 255, 255);">The University Hospital Institute of
Image-Guided Surgery (IHU Strasbourg) is searching for a scientist
to conduct research in federated learning for medical data to help
develop generalizable and efficient ML algorithms under the scope
of self-supervision, domain shift, improved data utility
detection, learning through noisy labelling.<span> </span><span
style="margin: 0px; padding: 0px; border: 0px; font: inherit;
vertical-align: baseline; color: rgb(0, 0, 0); background-color:
rgb(255, 255, 255); display: inline !important;">IHU has been in
the forefront of research in surgical AI with its
state-of-the-art facilities and multidisciplinary team of
computer scientists and research surgeons. </span>The candidate
will have the opportunity to work closely with researchers in the
space of surgical AI, to mentor and to shape research. <span
style="margin: 0px; padding: 0px; border: 0px; font: inherit;
vertical-align: baseline; color: rgb(0, 0, 0); background-color:
rgb(255, 255, 255); display: inline !important;">The candidate
will have the pleasure to live in Strasbourg, one of the most
beautiful and vibrant cities in Europe.</span></div>
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<div style="margin: 0px; padding: 0px; border: 0px; font:
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apply</div>
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<li>Please email your resume at
<a class="moz-txt-link-abbreviated" href="mailto:alexandros.karargyris@ihu-strasbourg.eu">alexandros.karargyris@ihu-strasbourg.eu</a> with the title
"Research Scientist in FL"</li>
<li>Position is open until filled </li>
<li>Initially, 2-year contract with a possibility to
extend or convert to permanent position<br
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<div style="margin: 0px; padding: 0px; border: 0px; font:
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<ul>
<li>Strong background in machine learning</li>
<li>Proven experience in Federated Learning through
publication(s) and/or code (e.g. Github) is a plus but
not a requirement</li>
<li>Background in medical data (e.g., imaging, health
records, genomics, etc.) is a plus but not a
requirement<br aria-hidden="true">
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<li>Python</li>
<li>Tensorflow, PyTorch, or Keras</li>
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<div style="margin: 0px; padding: 0px; border: 0px; font:
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<ul>
<li>Perform research in Federated Learning algorithms </li>
<li>Publish peer-reviewed papers </li>
<li>Participate in research meetings with top industry
partners and contribute code to open research
community (e.g. MLCommons) </li>
<li>Provide mentorship<br aria-hidden="true">
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inherit;">About the institute</div>
<span style="margin: 0px; padding: 0px; border: 0px;
font: inherit; vertical-align: baseline; color:
inherit;">The University Hospital Institute of
Image-Guided Surgery (IHU Strasbourg) i is a unique
research facility offering a true multidisciplinary
environment to innovate in the image-guided surgery
domain. Surgeons and engineers work closely together
on practical as well as moonshot research ideas.
Promising ideas are funded and supported internally,
competitive research grants or partnership programs,
while developed and validated ideas are translated to
products through licensing and startup spin-offs. The
institute has strong collaborations with academia and
industry. Located in the heart of Strasbourg’s
historic hospital campus, the IHU Strasbourg is an
international medical-surgical centre created in 2011,
specialising in minimally invasive approaches
(laparoscopy, flexible endoscopy, ultrasound,
percutaneous surgery). The IHU brings together care,
research, training, and technology transfer activities
in an exceptional setting for the benefit of patients.
Surgeons and engineers work in close collaboration on
applied and innovative research topics. Upstream
topics (TRL 0 to 2) are funded and supported
internally through competitive research grants or
partnership programmes. Mature topics (TRL 3 to 5) are
transformed into products through licensing and
spin-off companies. The Institute has strong
collaborations with academia and industry</span></div>
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vertical-align: baseline; color: inherit;"><span style="margin:
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</span></div>
<div style="margin: 0px; padding: 0px; border: 0px; font: inherit;
vertical-align: baseline; color: inherit;"><span style="margin:
0px; padding: 0px; border: 0px; font: inherit; vertical-align:
baseline; color: inherit;">About the lab</span></div>
<div style="margin: 0px; padding: 0px; border: 0px; font: inherit;
vertical-align: baseline; color: inherit;"><span style="margin:
0px; padding: 0px; border: 0px; font: inherit; vertical-align:
baseline; color: inherit;">The research group CAMMA
(Computational Analysis and Modelling of Medical Activities)
numbers approximately 30 researchers with interdisciplinary
backgrounds, led by Prof. Nicolas Padoy. CAMMA aims at
developing new tools and methods based on computer vision,
medical image analysis, and machine learning to perceive,
model, analyze, and support clinician and staff activities in
the operating room (OR) using the vast amount of digital data
generated during surgeries. CAMMA is a joint group of ICube at
the University of Strasbourg and the Institut
Hospitalo-Universitaire of Strasbourg (IHU Strasbourg). Our
offices are located on the campus of Strasbourg’s University
Hospital in the ultramodern facilities of IHU Strasbourg, a
walking distance from the beautiful historic city center of
Strasbourg. Due to its unique location and collaborations, the
group has privileged access to multiple resources for
high-performance computing, preclinical and clinical platforms
for fast prototyping, and offers new and modern office space
for its members.<br aria-hidden="true">
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