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Postdoctoral Position in Spatial Modeling of Porous Structures

Chalmers University of Technology has an opening Postdoc position. This fellowship is available for all students around the world. Applicants should apply before September 28, 2018.

Information about the research

The Division of Applied Mathematics and Statistics at the Department of Mathematical Sciences at Chalmers University of Technology and the University of Gothenburg, together with the Agrifood and Bioscience unit of RISE Research Institutes of Sweden, invites applications for one two-year postdoctoral position starting November 1, 2018, or as agreed. The successful candidate will be offered a one-year employment at Chalmers, followed by a one-year employment at RISE Agrifood and Bioscience.

The aim of the project is to develop new tools and methods for statistical modeling of random, heterogeneous, porous material structures. This involves both to work with two- and three-dimensional imaging data of real material structures and with simulation of virtual material structures inspired by real materials to understand the connection between structure and mass transport properties (diffusion and flow). The project constitutes part of a collaboration with several major Swedish industries, as well as with experimentalists in academia, and the methods and software that are developed within the project will be applied to real, industry-relevant materials used in for example hygiene products, packaging materials, pharmaceuticals, etc.

As part of the VINNExcellence Centre SuMo Biomaterials (SuMo), the project 'Material structures seen through microscopy and statistics' funded by the Swedish Foundation for Strategic Research, and the project 'Mass transport properties of soft porous granular materials' funded by the Swedish Research Council, many tools for image analysis, statistical characterization, and generation of virtual material structures have been developed. Further, within the SuMo Centre, state-of-the-art software for lattice Boltzmann-based diffusion and flow simulations is available.

The aim is to build upon the accumulated knowledge from these projects and:

(1) Develop new image analysis and segmentation algorithms for image data. Highly accurate automatic or semi-automatic image analysis methods are crucial for segmentation of imaging data of material structures. This is particularly important for 3D data where data size makes complete manual segmentation very time-consuming.

(2) Develop new spatial and spatio-temporal models for fiber materials, foams, granular media, etc, using knowledge acquired through studying real materials.

(3) Perform simulation studies of mass transport properties using available simulation tools developed in related projects together with new methods of generating material structures. Exploring material structures in the computer is important to avoid costly and time-consuming experimental studies.

The goal is a deep understanding of the relationships between microstructure and properties that will benefit both further research and applications.

This position is one of three postdoctoral positions within the new project CoSiMa, which is part of the SuMo Biomaterials centre (www.chalmers.se/sumo).

References

S Barman, D Bolin. A threedimensional statistical model for imaged microstructures of porous polymer films. Journal of Microscopy, 269, 247-258 (2018).

H Hbel, T Rajala, C Boissier, M Marucci, K Schladitz, C Redenbach, A Srkk. A three-dimensional anisotropic point process characterization for pharmaceutical coatings. Spatial Statistics, 22, 306-320 (2017).

M Rding, K Gaska, R Kdr, N Lorn. Computational screening of diffusive transport in nanoplatelet-filled composites: Use of graphene to enhance polymer barrier properties. ACS Applied Nano Materials, 1, 160167 (2018).

M Rding, E Schuster, K Logg, M Lundman, P Bergstrm, C Hanson, T Gebck, N Lorn. Computational high-throughput screening of fluid permeability in heterogeneous fiber materials. Soft Matter, 12, 6293-6299 (2016).

About the division and the department

At the Division of Applied Mathematics and Statistics we conduct research at a high international level in areas such as biomathematics, bioinformatics, computational mathematics, optimisation, mathematical statistics, kinetic theory. More information about our research groups is available on the website http://www.chalmers.se/en/departments/math/research/research-groups/

We have an international environment with frequent exchanges with other universities around the world. The department provides a friendly, creative, and supportive atmosphere with a steady flow of international guests. At the division there are many committed teachers with extensive and broad experience of all aspects of higher education. Together with the Divisions of Algebra and Geometry and Analysis and Probability we form the academic part of the department of Mathematical Sciences, which is a joint department of Chalmers and the University of Gothenburg, and one of the largest in mathematics in the Nordic countries with a faculty core of about 80. More information about us is available on the website http://www.chalmers.se/en/departments/math/.

At the Agrifood and Bioscience unit at RISE Research Institutes of Sweden we conduct research and development in food, agriculture, and bioscience related topics including quantitative microscopy, image analysis, computational materials science, hetereogeneous and viscoelastic materials, microbiology and food processing. The unit comprises about 100 people, and is part of the division of Bioscience and Materials at RISE Research Institutes of Sweden. More information about us is available on the website

http://www.sp.se/en/units/risebiovet/fb/Sidor/default.aspx

Major responsibilities

You are expected to pursue a vigorous research program and collaborate with our researchers.

During the employment at the Department of Mathematical Sciences, we offer you the possibility that up to 20 % of your work may be spent on teaching. RISE Agrifood and Bioscience does not offer teaching.

Full-time temporary employment. The position is limited to a maximum of two years (1+1).

Qualifications

You should have a Ph.D. in Applied Mathematics, Mathematical Statistics, Computational Science, possibly also Physics, or equivalent, completed before the starting date of employment and not earlier than three years before the application deadline. Fluency in English is expected. Experience in image analysis and processing, machine learning, spatial statistics, and good programming skills is meriting.

Read more about working at Chalmers and our benefits for employees.

Application procedure

The application should be marked with Ref 20180454 and written in English. The application should be sent electronically and be attached as pdf-files, as below:

CV: (Please name the document as: CV, Surname, Ref. number) including:
- CV, include complete list of publications
- Previous teaching and pedagogical experiences
- Two references that we can contact.

Personal letter: (Please name the document as: Personal letter, Family name, Ref. number) including:
- 1-3 pages where you introduce yourself and present your qualifications.
- Previous research fields and main research results.
- Future goals and research focus. Are there any specific projects and research issues you are primarily interested in?

Other documents:
- Attested copies of completed education, grades and other certificates.

Application deadline: 28 September, 2018

For questions, please contact:

Deputy head of Division, Stig Larsson, stig@chalmers.se

Aila Srkk, aila@chalmers.se

Magnus Rding, magnus.roding@ri.se


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