Uni Distance Suisse, as an accredited university institute in accordance with the Swiss Higher Education Act (HEd A), has been offering bachelor’s and master’s degrees programs and continuing education and training programs in the faculties of Law, Psychology, Mathematics and Computer Science, Economics and History for over 30 years. These programs can be attended in parallel with family life, professional or sporting career, in a flexible distance learning model.
Uni Distance Suisse is dedicated to the highest quality standards in teaching and research. With over 2300 students, it is the leading institution in the field of distance education in Switzerland. It has more than 450 employees, over 350 of whom are involved in teaching and research activities.
The recently approved SNF project, entitled “Numerical Methods for Efficient Acoustic Metamaterial Design” aims to design acoustic metamaterials which are used to manipulate sound waves, with the objective of, for instance, mitigating sound within the audible frequency spectrum. For the optimal design of such metamaterials our goal is to optimise models from (mixed) boundary/finite element discretisations. This leads to very rich structures in the underlying linear systems of equations. The aim of the project consists of fully exploiting these structures for efficient matrix storage as well as in the numerical solution techniques. These techniques will open up the possibility to apply parametric model reduction methods which are the basis for determining an optimal acoustic metamaterial. The project will be carried with our project partner Prof. Dr Steffen Marburg (Chair of Vibroacoustics of Vehicles and Machines, Technical University of Munich, Germany).
We are looking for a:
Research Assistant (with possibility to obtain a Ph D) (80%)
Place of work: Brig. Remote work is possible, but regular presence (~2 days per week) in the office in Brig is expected.
Start of work: upon agreement, preferably in the first quarter of 2025.

Your tasks

• Development of numerical methods for efficient acoustic metamaterial design.
• Efficient implementation and testing of the methods, e.g., in Python and/or Matlab.
• Preparation of scientific manuscripts for submission in top journals in the field.
• Presentation of the results at conferences and workshops.
• Teaching is possible on a voluntary basis.

Your profile

• A Master of Science degree (or equivalent) in (applied) mathematics, scientific computing or engineering.
• Strong programming skills, e.g., in Python or Matlab.
• Strong interest in working on a very applied mathematics project with a regular exchange with partners from engineering.
• Background in one or more of the following subfields: numerical linear algebra (e.g., rank-structured matrices, tensor techniques), model reduction, numerical methods for partial differential equations, machine learning, numerical optimisation. Experience in applying these techniques in engineering applications and familiarity in interdisciplinary work are an additional plus.
• Highly independent working style, stamina, and curiosity; reliability and care in the preparation of research results.
• Very good English skills, additional skills in German and/or French are an additional plus.

We offer

• Versatile and varied work in a university environment.
• Attractive employment conditions.
• Collaboration in a motivated team with exciting further training opportunities.

We look forward to receiving your complete application by e-mail to Prof. Dr Matthias Voigt at matthias.voigt@fernuni.chby 15th December 2024 at the latest.
A complete application package consists of the following documents: a cover letter indicating your motivation for the application, a CV, a two-page research statement summarising the topic and outcome of your M.Sc. thesis and your general research interests, degree transcripts, contact data of one or two references (letters of reference will be collected for short-listed candidates).
Applications will be considered from people who are resident in Switzerland or are considering moving to Switzerland.
For further information, please contact Prof. Dr Matthias Voigt: matthias.voigt@fernuni.ch.