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PhD Scholarship Position in Mathematical Modeling for Personalized Nutrition

A new PhD position in communicable diseases is available at Chalmers University of Technology. Successful candidate will have funding to work and study for 5 years in Sweden. Applications are welcome before March 22, 2019.

Information about the research

The Division of Food and Nutrition Science (FNS) at Department of Biology and Biological Engineering at Chalmers together with the Fraunhofer-Chalmers Centre (FCC), is recruiting an institute PhD student for a project on mathematical modeling for personalized nutrition. Both FNS and FCC carry out world-class research and industrial projects where FNS focus is on on nutritional solutions for disease prevention and FCC focus is on using mathematics as a technology. For more information, see our websites http://www.chalmers.se/bio and http://www.fcc.chalmers.se

We are currently looking for a highly motivated individual to join us in an exciting project where mixed effects dynamical systems modelling will be applied on metabolomics and gut microbiota data from controlled dietary intervention studies. This will let us identify groups of individuals with specific metabolic phenotypes and predictive biomarkers of such groups to help guide towards optimal personalized diets. Another key aspect is to develop and extend mathematical methods to model dynamic changes in metabolic risk factors as a function of the metabolome and other determinants. This will enhance our understanding of individual variation in dynamic metabolic responses to dietary intakes and how this affects cardiometabolic risk. Our vision is that developed tools within 5 years can be used to facilitate personalized dietary advice for improved prevention of non-communicable diseases as well as result in tailored foods for groups of individuals with similar needs.

An integrated framework has been developed at FCC for advanced mixed effects dynamical systems modeling, mainly sofar with applications in the pharmaceutical industry, which provide means to describe dynamic processes using both ordinary and stochastic differential equations. Learning dynamical models from data includes maximum likelihood estimation and Bayesian approaches using both parametric and non-parametric methods. Models can be fitted to data from single individuals as well as ensembles of data records from individuals assumed to be governed by the same mechanistic descriptions but with individual parameters (so called nonlinear mixed effects models). In this project the student will also extend and adapt the framework in different ways to improve its performance and application to personalized nutrition when applied to scientifically challenging problem and data set(s), e.g., by exploring the use of particle Markov Chain Monte Carlo methodology, Gaussian process learning, and probabilistic programming.

The project will be performed in collaboration between the Fraunhofer-Chalmers Centre and Food and Nutrition Sciences at the Department of Biology and Biological Engineering. The PhD student will be enrolled in a graduate school at the Department of Biology and Biological Engineering.

Major responsibilities

As a PhD student you will be part of an international research environment while you expand your knowledge of the field and write your thesis. You will work together with a team of researchers and engineers with a thorough understanding of both applied mathematics and food & nutrition science. You are a team player with strong interest in mathematics and its use in applications, but are also expected to work autonomously, to develop your own ideas and communicate results to the scientific community. Totally, the graduate programme will comprise 4 years of study and research.

Your major responsibilities are to pursue your own doctoral studies. You are expected to develop your own scientific concepts and communicate the results of your research verbally and in writing, both in Swedish and in English.

Full-time temporary employment at the Fraunhofer-Chalmers Centre.The position is limited to a maximum of 4 years.

Qualifications

Applicants must have a strong background in the mathematical sciences. A master’s degree or a 4-year bachelor’s degree or an equivalent competence is required at the beginning of the employment.

Concurrent method development and implementation of algorithms is integral to the applied reseach carried out at FCC and good programming skills (e.g., Python, Mathematica, R) are therefore required.

In your application you should include all relevant work such as bachelor’s or master’s thesis and articles (provide an English summary if necessary) that you have authored or co-authored. Evidence of mathematical problem solving skills is significant, besides course grades.

The bachelor’s level teaching is normally in Swedish, although the teaching at the master’s and PhD levels is in English. Thus, good language skills are required.

If Swedish is not your native language, you should be able to teach in Swedish after two years. Chalmers offers Swedish courses.

Chalmers offers a cultivating and inspiring working environment in the dynamic city ofGothenburg.

Read more aboutworking at Chalmersand ourbenefitsfor employees.

Application procedure

The application should be marked with Ref 20190109 and written in English.

CV: (Please name the document: CV, Family name, Ref. number)

CV

Other, for example previous employments or leadership qualifications and positions of trust.

Two references that we can contact.

Personal letter: (Please name the document as: Personal letter, Family name, Ref. number)

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?

Copies of bachelor and/or master's thesis.

Attested copies and transcripts of completed education, grades and other certificates, eg. TOEFL test results.

Application deadline: 22 March 2019

Rikard Landberg, food and nutrition science, rikard.landberg@chalmers.se

Mats Jirstrand, Fraunhofer-Chalmers Centre, matsj@fcc.chalmers.se


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