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The research group Analytics & Mixed-Integer Optimization at <br>
Friedrich-Alexander-Universitaet Erlangen-Nuernberg (FAU), Germany,
<br>
invites applications for a full-time (100% TV-L E13)<br>
<br>
PhD Position in Mathematics (Discrete Optimization)<br>
<br>
at the Department of Data Science / Mathematics. The position is to
be filled as soon as possible for an initial period of three years.
The successful applicant will work in a research project on the<br>
<br>
Optimization of Logistics and Production Processes in the Food
Industry<br>
<br>
in cooperation with a variety of companies from the food sector. The
focus of the project will be the development of optimization models
and exact solution methods from mixed-integer linear and non-linear
programming (MIP / MINLP) for the optimal allocation of resources in
food production and transport, such as mixture/pooling problems. The
mathematical work in this project will focus on the structural
analysis and algorithm development for these problems, drawing e.g.
upon polyhedral analysis, graph theory and decomposition methods.
The treatment of data uncertainties occurring in these problems will
likely require the development of robust or stochastic optimization
approaches. The PhD candidate will also be part of the Ada Lovelace
Center for Analytics, Data and Applications, a research network on
artificial intelligence founded by Fraunhofer, FAU and LMU Munich,
see <a class="moz-txt-link-freetext" href="https://www.ada-lovelace-center.de">https://www.ada-lovelace-center.de</a><br>
<br>
Applicants should have completed their master studies in
mathematics, ideally with specialization in discrete optimization.
Prior experience with MINLPs is desired but not a requirement.
Applicants should have programming experience, e.g. in Python, and
should have experience in the use of optimization solvers like
Gurobi, CPLEX or SCIP. Fluency in both German and English is
required. We seek excellent, open-minded and team-spirited PhD
candidates who are interested in both the theory of discrete
optimization as well as the practical solution of optimization
problems in cooperation with industry.<br>
<br>
The research group<span class="formattedtext"> Analytics &
Mixed-Integer Optimization at FAU focusses on the development of
mathematical optimization models for industrial applications. This
includes the theoretical analysis of the models, the design and
implementation of efficient solution algorithms and their transfer
into practice. Especially, we use techniques from mixed-integer
linear and non-linear optimization, combined with methods from
robust, stochastic, multilevel and combinatorial optimization. Our
application partners come from all sectors of industry, e.g.
logistics and production, mobility or energy systems. For further
information, e.g. about our team and current research projects</span>,
see our homepage:<br>
<a class="moz-txt-link-freetext" href="https://www.edom.fau.de">https://www.edom.fau.de</a><br>
<br>
Please send your complete application documents (motivation letter
and detailed CV written in German, transcript of records for BSc and
MSc courses, copy of bachelor and master thesis, certificates, etc.)
in electronic form<br>
until 30 September 2021 to:<br>
<a class="moz-txt-link-abbreviated" href="mailto:Andreas.Baermann@fau.de">Andreas.Baermann@fau.de</a><br>
<br>
<br>
Postal address:<br>
Dr. Andreas Baermann<br>
FAU Erlangen-Nuernberg<br>
Lehrstuhl fuer Analytics & Mixed-Integer Optimization<br>
Cauerstrasse 11<br>
91058 Erlangen, Germany<br>
<br>
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