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PhD position in Physics-based machine learning for real-time simulation update

05.10.2020 - RWTH Aachen, Germany

Research Assistant/Associate (w/m/d) position in Physics-based machine learning for real-time simulation update. Work is mainly conducted at the research unit Computational Geoscience and Reservoir Engineering (CGRE) at RWTH Aachen University, with planned secondments at industry partners and ETH Zurich. The CGRE team consists of 10 people of various scientific background, including geology, geophysics, and engineering. You can expect a very diverse and challenging job in an international and multidisciplinary working environment. RWTH Aachen University is part of the ABC/J Geoverbund, and therefore well connected with Cologne and Bonn Universities and the Forschungszentrum Jülich.The position is to be filled 01.01.2021 until limited to 3 years. It is a full-time position (EG 13 TV-L) with the possibility of a part-time contract upon request. Please submit your application no later than October 31.

Our Profile

Geothermal operations require reliable predictions of temperature and pressure fields to ensure sustainable and safe long-term operation. In this project, you will develop a numerical method to enable a real-time update of hydrothermal simulations. The aim is to react quickly to new measurements and to adjust results accordingly, in order to provide the best possible up-to-date prediction of the system state for subsequent decisions. The developments are based on existing open-source hydrothermal simulations in an efficient High-Performance Computing Finite Element Framework (MOOSE). This code will be adjusted to the geothermal simulation requirements and linked to a physics-based machine learning approach. Different geological parameterization approaches can then be tested and implemented in the workflow, with the aim to train machine learning systems for a real-time update of the hydrothermal state of a geothermal system. The work contains innovative and novel aspects from applied mathematics and computer science, with strong links to geophysical and geological data. The project is therefore interdisciplinary in nature and will have strong links to other projects within the ITN EASYGO.

Work is mainly conducted at the research unit Computational Geoscience and Reservoir Engineering (CGRE) at RWTH Aachen University, with planned secondments at industry partners and ETH Zurich. The CGRE team consists of 10 people of various scientific background, including geology, geophysics, and engineering. You can expect a very diverse and challenging job in an international and multidisciplinary working environment. RWTH Aachen University is part of the ABC/J Geoverbund, and therefore well connected with Cologne and Bonn Universities and the Forschungszentrum Jülich. RWTH is an equal opportunity employer. Thus, we specifically encourage applications of qualified women and minorities.

How to apply

Please submit your application no later than October 31 as a single PDF file named EASYGO_10_YourLastname_YourFirstname.pdf containing a motivation letter, CV, M.Sc. certificate and grades for the individual courses (highlighting courses relevant for this position) to applications@cgre.rwth-aachen.de. Language certificates and documents showing practical experience in the field are desirable. Please note that this file will be shared with members of the EASYGO recruitment committee at all four participating IDEA League universities and one industry representative.


Please note that EU ITN mobility rule applies (see guide for applicants here: https://ec.europa.eu/research/participants/data/ref/h2020/other/guides_for_applicants/h2020-guide-appl-msca-itn_en.pdf), meaning that applicants must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting beneficiary for more than 12 months in the 3 years immediately before the recruitment date.


Your Profile

- University degree (Master or equivalent) in geosciences, engineering, computer science or related subjects
- Experience with numerical simulations (preferably with Finite Elements) in theory and practice
- Interest in coupled process simulations in geosciences
- Experience with High Performance Computing is an advantage
- Good English knowledge (written & spoken)
- High degree of initiative, discipline and team spirit
- Ability to work scientifically and independently


Your Duties and Responsibilities

- Adjust existing hydrothermal simulation codes (in MOOSE framework. C++) to geothermal problems
- Train different surrogate models with focus on physics-based approaches (e.g. reduced basis method)
- Integrate geological parameterizations, e.g. geological layers and spatial property distributions
- Enable real-time simulation adjustments during operational and monitoring phase
- Active participation in the various training and networking opportunities provided by EASYGO and the IDEA League doctoral school
- Presentation of own research at selected scientific conferences and publication in peer-reviewed journals


What We Offer

The successful candidate will be employed under a regular employment contract.
The position is to be filled 01.01.2021 until limited to 3 years.
This is a full-time position with the possibility of a part-time contract upon request.
The successful candidate has the opportunity to pursue a doctoral degree in this position.
The salary corresponds to pay grade EG 13 TV-L of the German public service salary scale (TV-L).
RWTH is a certified family-friendly University. We support our employees in maintaining a good work-life balance with a wide range of health, advising, and prevention services, for example university sports. We also offer a comprehensive continuing education scheme and a public transportation ticket available at a significantly reduced price.
RWTH is an equal opportunities employer. We therefore welcome and encourage applications from all suitably qualified candidates, particularly from groups that are underrepresented at the University. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of national or ethnic origin, sex, sexual orientation, gender identity, religion, disability or age. RWTH is strongly committed to encouraging women in their careers. Female applicants are given preference if they are equally suitable, competent, and professionally qualified, unless a fellow candidate is favored for a specific reason.
As RWTH is committed to equality of opportunity, we ask you not to include a photo in your application.
You can find information on the personal data we collect from applicants in accordance with Articles 13 and 14 of the European Union's General Data Protection Regulation (GDPR) at http://www.rwth-aachen.de/dsgvo-information-bewerbung

See link below for full job announcement

https://www.cgre.rwth-aachen.de/go/id/qpap/file/32500/lidx/1/


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