Description

Advertising division: IEK-6 - Nuclear Waste Management and Reactor Safety

Reference number: 2022-181

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job (pdf)

The Institute of Energy and Climate Research - Nuclear Waste Management and Reactor Safety (IEK-6) performs cutting-edge research in the fields of nuclear waste management and safety. We apply innovative experimental and computational approaches to analyse and interpret complex coupled hydro- geochemical processes relevant to radionuclide release and transport in the near- and far-field of geological repositories for radioactive wastes. Microfluidic lab-on-a-chip systems with real time imaging in combination with reactive transport modeling are decisive tools to generate spatio-temporal insights into coupled hydro-geochemical processes e.g. mineral precipitation in porous media. Our aim is to create a Digital Twin Kit, a modular platform enabling existing reactive transport codes to assess hydro-geochemical processes from time-lapse microscopy imaging live and in real time. The kit will provide an expanded tool-box for the experimentalist that will enable a quick evaluation of the results and prognosis about optimal control of the experiments while they are running.

We are looking to recruit a

Postdoc - Machine Learning and Image Processing

Your Job:

The first building block of the Digital Twin Kit is an image analysis system able to fully characterize the mineral growth and porosity changes in the microfluidic reactors from image stacks generated by time-lapse microscopy, Raman and X-ray CT imaging. In this context your work comprises:

Application of machine learning to establish an automated image processing workflow for data evaluation and creation of input data for numerical reactive transport simulations

Development of a standalone software including libraries with referenced minerals for an automated image processing of evolving porous media

Collaboration with international institutions for the development of the interface of the standalone software with the flow solvers

Presentation of the results at scientific conferences and in scientific publication

Your Profile:

Ph.D. in Computer sciences, applied Mathematics, (applied) Physics, Computational earth sciences or a related discipline

Experience in AI based image processing (e.g. convolutional neural networks)

Practical experience with programming languages (such as C, C++, Python or Fortran)

Knowledge in the imaging of porous media is desirable

Ability to work in an international multidisciplinary team is essential

Excellent English communication and writing skills

Our Offer:

We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We support you in your work with:

A large research campus with green spaces, offering the best possible means for networking with colleagues and pursuing sports alongside work

Comprehensive training courses and individual opportunities for personal and professional further development

Extensive company health management

Ideal conditions for balancing work and private life, as well as a family- friendly corporate policy

30 days of annual leave and provision for days off between public holidays and weekends (e.g. between Christmas and New Year)

Targeted services for international employees, e.g. through our International Advisory Service

We offer you an exciting and varied role in an international and interdisciplinary working environment within the framework of a position limited to 2 years. Salary and social benefits in conformity with the provisions of the Collective Agreement for the Civil Service (TVöD). Depending on the applicant`s qualifications and the precise nature of the tasks, salary grade 13 TVöD-Bund.

We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation / identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realize their potential is important to us.