Many technologically important material properties are closely related to disorder and short-range structural correlations. Diffuse scattering observed in a diffraction experiment on crystalline materials contains the information on dynamic and static disorder. Relating this information to the underlying structural disorder is a challenging task, particularly in the case of single crystal diffraction data where the information extends towards 3-d space. Machine learning offers promising approaches for the solution of complex problems of disorder, ultimately aiming at general and automated workflow for the analysis of single-crystal diffuse scattering. In this project, you will have the opportunity to contribute towards reaching this challenging aim.
Your tasks include:
- Deducing numerous models of structural disorder based on the periodic average structure, crystal chemistry, and complementary information
- Generation of a dataset to train ML models
- Simulation of the corresponding diffraction patterns and comparison to experimental data of a prototypic compound
- Develop a generalized machine learning based workflow for the interpretation of diffuse scattering
Your Profile:
- Completed Master`s degree in crystallography, material science, physics, chemistry, or a related field
- You have an interest in scattering methods, solid-state materials and ideally also knowledge in the field of programming, maybe even machine learning and artificial intelligence
- Prior knowledge of machine learning is not required, but considered an asset
- You have an independent and responsible way of working, commitment, high degree of teamwork, as well as enjoyment of cooperative collaboration
- Very good command of written and spoken English with extensive vocabulary is required (at least B2 level according to the CEFR)
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 offer ideal conditions for you to complete your doctoral degree:
- ENVIRONMENT: A dynamic, international, multidisciplinary and motivated team at one of the largest research institutions in Europe
- RESEARCH & INFRASTRUCTURE: Access to excellent scientific and technical facilities; possibility to perform experiments at large scale infrastructures (synchrotron and neutron sources)
- NETWORKING & EXCHANGE: Participation in (international) conferences, enabling you to build and expand your scientific network
- PERSONAL DEVELOPMENT: Integration to the JuDocs Center ( Jülich Center for Doctoral Researchers and Supervisors ) offering onboarding, qualification opportunities, project monitoring, and counselling; access to additional scientific and professional trainings, as well as options for international research stays
- WORK-LIFE BALANCE: We offer flexible working hours to help you balance your professional and personal life. You also have the option of flexible working (in terms of location), which is generally possible after consultation and in line with upcoming tasks and (on-site) appointments
- VACATION: You will receive 30 days of vacation
- FAIR REMUNERATION: Depending on your qualifications and assigned responsibilities, you will be classified according to pay group 13 (75%) of the TVöD-Bund. Additionally, you will receive a special payment (“Christmas bonus”) amounting to 75% of one month’s salary.
- FIXED-TERM: The position is initially for a fixed term of 3 years.
- SUPPORT FOR INTERNATIONAL EMPLOYEES: Our International Advisory Service makes it easier for international employees to get started and supports you with all questions related to starting work and living in Germany
In addition to exciting tasks and a collegial working environment, we offer you much more: https://go.fzj.de/benefits
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.
