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The <b>Research Group on Applied Mathematics and Optimization</b>
at the Faculty of Mathematics of<br>
the University of Vienna, headed by Radu Ioan Bot, has its core
research areas in Nonsmooth and<br>
Convex Optimization. Currently it offers<br>
<br>
<b>1 Doctorate Research Position (3 years) at the</b><b><br>
</b><b>Faculty of Mathematics, University of Vienna</b><br>
<br>
within the FWF-funded research project <b>Employing Recent Outcomes
in Proximal Theory Outside</b><b><br>
</b><b>the Comfort Zone</b>.<br>
<br>
The main scientific target of the project is to employ recent
advances concerning some classical<br>
techniques used so far mainly for iteratively minimizing convex
functions in Hilbert spaces to research<br>
fields lying outside their comfort zone. These methods evolve around
the notion of proximality, which<br>
relies on evaluating a certain regularization of the addressed
mathematical object. Due to its reliability,<br>
simplicity and accuracy, the proximal theory was successfully
employed for solving nondifferentiable<br>
convex optimization problems and monotone inclusions with complex
structures as well, proving a<br>
strong positive impact on the treatment of real-life applications
with high-dimensional data.<br>
<br>
The research themes to be addressed in this project range from the
employment of the paradigm of<br>
proximality in broader frameworks like considering generalized
distances, working in more general<br>
underlying spaces and addressing the direct solving of
multiobjective optimization problems to the<br>
approach of monotone inclusions problems via first- and second-order
dynamical systems. The<br>
expected results should have impact beyond the corresponding
research areas both in mathematical<br>
fields like ordinary differential equations, partial differential
equations, optimal control, functional<br>
analysis, game theory, equilibrium problems and optimal transport
theory, and in the solving of real-life<br>
problems arising in optimal location selection, image processing,
machine learning, quantification of<br>
risk, network communication and video processing.<br>
<br>
The position is available from <b>September 1st, 2016</b>. The
salary is as suggested by the FWF<br>
according to a doctorate position. The working load for the project
is 30 hours per week. The deadline<br>
for application is <b>June 30th, 2016</b>.<br>
<br>
<b>Required Qualifications</b><br>
<br>
The candidates should have a master degree (or equivalent) in
Mathematics, a solid theoretical<br>
background and strong computer skills. Fluency in the English
language has to be proven.<br>
Applications (including a letter of motivation, curriculum vitae,
the master thesis, peer reviewed<br>
research publications, copies of academic certificates and a letter
of recommendation) should be sent<br>
to: <u><a class="moz-txt-link-abbreviated" href="mailto:min.hadler@univie.ac.at">min.hadler@univie.ac.at</a>.</u> More information can be found
on <u><a class="moz-txt-link-freetext" href="http://www.mat.univie.ac.at/~rabot">http://www.mat.univie.ac.at/~rabot</a></u>.<br>
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