PhD Scholarship Position in Learning Dynamical Systems in Drug Discovery

Outstanding international students are invited to apply for a PhD scholarship in applied mathematics at Chalmers University of Technology. The funds for this position are available for 2 years. Potential candidates should apply before March 17, 2019.

The Department of Mathematical Sciences pursues internationally successful research and an extensive education.

Mathematics is fundamental to science and engineering and has an increasingly prominent part in other disciplines as well. Mathematics is also a subject in itself, and fundamental research is a necessary condition for future applications. The Department is part of both Chalmers University of Technology and the University of Gothenburg and is situated in the middle of Campus Johanneberg. It is the largest mathematics department in the Nordic countries and has about 200 employees, with a number of research groups in mathematics and mathematical statistics which together provide a creative and cross-fertilizing setting. Information about the project

The Department of Mathematical Sciences at Chalmers University of Technology and University of Gothenburg, together with the Fraunhofer-Chalmers Centre (FCC), is recruiting an industrial PhD student for a project on learning dynamical systems in drug discovery. Both the Department of Mathematical Sciences and FCC carry out world-class research and industrial projects with a focus on using mathematics as a technology. For more information, see our websites http://www.chalmers.se/math/ and http://www.fcc.chalmers.se

We are currently looking for a highly motivated individual to join us in an exciting project working closely with the pharmaceutical industry to proceed beyond state-of-the-art modeling and simulation methodology and tools for pharmacokinetic and pharmacodynamics processes. A quantitative description of the dynamics of a pharmacological compound in the blood after drug administration, typically the plasma concentration of a drug as a function of time, is of fundamental importance in drug development. The task of developing mathematical models of this dynamical process is known by the name pharmacokinetic (PK) modeling. The time-varying plasma concentration may in turn be linked to the pharmacological effect, e.g., less pain, reduction in bacteria, or reduced fever using so called pharmacodynamic (PD) modeling.

An integrated framework has been developed at FCC for advanced PK/PD modeling and simulation, which provide means to describe PK/PD 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 extend and adapt the framework in different ways to improve its performance when applied to an industrially relevant 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, the Department of Mathematical Sciences, and Grnenthal. The PhD student will be enrolled in a graduate school in the Department of Mathematical Sciences. The project is carried out as part of an existing collaboration between FCC and Grnenthal. Furthermore, Grnenthal supports the project with data and challenging applied problems and there will be opportunities for shorter or longer visits to the company during the course of the project.

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 pharmaceutical applications. You are a team player with strong interest in industrial applications, but are also expected to work autonomously, to develop your own ideas and communicate results to the scientific community. In addition, the position will normally include 10% departmental work, mostly teaching duties. The position leads to a licentiate in engineering (LicEng) exam with a total time of 2 years including 10% teaching duties. Prolongation of the project leading to a PhD degree will be considered based on interest and available funding.

Full-time employment at FCC. Starting date: 1 June, 2019, or according to agreement.

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.

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

Application procedure

The application should be marked with Ref 20190083 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: 17 March 2019

Stig Larsson, tillmpad matematik och statistik, stig@chalmers.se

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

Marija Cvijovic, tillmpad matematik och statistik, marija@chalmers.se

Deadline: March 17, 2019
Apply Link:http://tinyurl.com/y362gka8

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