Doctoral Researcher Position
(m/f/d, 100%, E 13 TV-L, temporary for the duration of 3.5 years)
Advanced Surrogate Modelling for Biological Systems
The Cluster of Excellence "Data-Integrated Simulation Science" (EXC 2075) is an interdisciplinary research center with more than 200 scientists of different ages, gender identities, nationalities and different subject areas, jointly performing research towards a common goal: We target a new class of modeling and computational methods based on available data from various sources, in order to take the usability, precision and reliability of simulations to a new level. The open doctoral researcher position is integrated into the Graduate School of the Cluster.
The doctoral researcher will work on the topic “Data-integrated training of surrogate models for uncertainty quantification and diagnostic evaluation of complex biological systems models”. The project will be embedded into SimTech’s project network PN2 “In silico models of coupled biological systems”, but will offer the opportunity to also collaborate within the University of Stuttgart, across German Universities and internationally on a wide range of possible application case studies (e.g. from the fields of hydrogeology, soil-plant modelling, or cognitive science). The doctoral researcher will become a member of the Junior Research Group for Statistical Model-Data Integration of Dr. Anneli Guthke, and will be co-supervised by Dr. Paul-Christian Bürkner, Junior Research Group Leader for Bayesian Statistics (both groups located at SimTech).
- Development of methods to advance surrogate model training, surrogate-based Bayesian uncertainty quantification and diagnostic evaluation of complicated simulation models, building on tools from simulation science and machine learning
- Development of computer code (e.g. in MATLAB, R or Python) to implement the proposed methods
- Testing and evaluation of the developed methods and code on selected case studies
- Close cooperation with other scientists within the research group, at the Cluster of Excellence SimTech, and internationally
- Publication of research results in international scientific journals and conference proceedings
- Active participation in national and international conferences
- Very good degree in a field with strong quantitative focus (e.g., simulation science, mathematics, computer science, biology, environmental science)
- Strong interest in research questions focused on simulation, machine learning, and statistics
- Previous experience in applied statistics, numerical simulation or machine learning
- Ideally previous experience in Bayesian statistics
- Previous experience in at least one programming language common in quantitative fields (e.g., MATLAB, R, Python, Julia, or C++)
- Proficient English skills (spoken and written); German skills are an asset but not required
- High amount of commitment to pursue a PhD, passion for scientific challenges, willingness and ability to work both independently and in a team
- An inspirational and supportive research environment at the Cluster of Excellence SimTech with ample networking opportunities
- A nationally and internationally well-connected research group
- Fully funded conference visits and a fully funded research stay abroad
- Diverse and responsible tasks in a growing interdisciplinary and intercultural team
- Training programs to support your first steps as an early career scientist
Please submit your complete application, including one-page motivation letter, academic CV, one letter of reference, as well as academic certificates and transcript of records, via firstname.lastname@example.org and email@example.com until January 26th, 2022. If you have any questions regarding this application, please contact us via firstname.lastname@example.org.
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At the University of Stuttgart and the Cluster of Excellence EXC 2075, we actively promote diversity among our employees. We have set ourselves the goal of recruiting more women scientists and employing more people with an international background, as well as people with disabilities. We are therefore particularly pleased to receive applications from such people. Regardless, we welcome any good application.
Women who apply will be given preferential consideration in areas in which they are underrepresented, provided they have the same aptitude, qualifications and professional performance. Severely disabled applicants with equal qualifications will be given priority.
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