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Frank Schreiber

Prof. Dr. Dr. h.c. at University of Tübingen

University of Tübingen

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Germany

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Research Interests

Condensed Matter Physics

10%

Physics

50%

X-ray Scattering

50%

Neutron Scattering

50%

Chemistry

50%

Machine Learning

40%

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Positions5

Publisher
source

Frank Schreiber

University Name
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University of Tübingen

PhD Student/Doctoral Candidate in Protein Dynamics Using X-ray and Neutron Scattering

The "Physics of molecular and biological matter" group at the University of Tübingen is seeking a highly motivated PhD student or doctoral candidate to join their research on protein dynamics. The group, led by Prof. Dr. Dr. h.c. Frank Schreiber, specializes in the physics of molecular and biological matter, employing advanced X-ray and neutron scattering techniques. Their research spans materials for photovoltaics, proteins in solutions and at interfaces, complex nano-structured materials, and the development of machine learning tools for efficient experimental data analysis. The successful candidate will focus on understanding the structure and dynamics of protein molecules in concentrated solutions. The project involves the use of Small-Angle X-ray Scattering (SAXS), X-ray Photon Correlation Spectroscopy (XPCS), Quasi-Elastic Neutron Scattering (QENS), and Dynamic Light Scattering (DLS) to investigate protein behavior. The role includes sample preparation, preliminary characterization using laboratory X-ray setups, participation in experiments at leading large-scale X-ray and neutron facilities (such as PETRA III, EuXFEL, ESRF, and ILL), and data analysis. The candidate will also have opportunities to present results at conferences and in scientific publications. Applicants should possess a Master’s degree in physics or chemistry (or equivalent), demonstrate interest in materials science, and have strong written and spoken English skills. Experience with programming (especially Python), practical laboratory skills, and enthusiasm for experimental work are highly valued. The ability to work independently and as part of a team is essential. While knowledge of German is not required, it is considered an advantage. The position is funded at the E13 TV-L salary scale (50-75%) for three years and offers the chance to work in an international, collaborative environment with access to state-of-the-art laboratories and equipment. The University of Tübingen is recognized as a University of Excellence in Germany, with a vibrant academic community and a commitment to diversity and equal opportunity. The city of Tübingen offers a rich student life, cultural events, and beautiful surroundings. To apply, candidates should send a single PDF file containing a cover letter, CV, and transcript of records to the specified email address. The position is available immediately and will remain open until filled. For further details about the group and research activities, visit the group website or the DAAD application page .

Publisher
source

Frank Schreiber

University Name
.

University of Tübingen

PhD Student in Physics of Molecular and Biological Matter – Protein Dynamics

The Physics of Molecular and Biological Matter group at the University of Tübingen, led by Prof. Dr. Dr. h.c. Frank Schreiber, is seeking a motivated PhD student to join their internationally recognized research team. The group specializes in the study of molecular and biological matter using advanced X-ray and neutron scattering techniques, with research areas spanning materials for photovoltaics, protein dynamics in solutions and at interfaces, complex nano-structured materials, and the development of machine learning tools for efficient experimental data analysis. This PhD project focuses on understanding the structure and dynamics of protein molecules in concentrated solutions. The successful candidate will employ a range of experimental techniques, including Small-Angle X-ray Scattering (SAXS), X-ray Photon Correlation Spectroscopy (XPCS), Quasi-Elastic Neutron Scattering (QENS), and Dynamic Light Scattering (DLS), to investigate protein behavior. The role involves sample preparation, preliminary characterization using laboratory X-ray setups, participation in measurement campaigns at world-leading synchrotron and neutron facilities (such as PETRA III, EuXFEL in Hamburg, ESRF, and ILL in Grenoble), and analysis and presentation of scientific results at conferences and in publications. The position offers a highly collaborative and international environment within the Institute of Applied Physics, access to well-equipped laboratories, and opportunities to contribute to top scientific experiments and develop new data analysis tools. Candidates will also have the chance to pursue their own research ideas using unique experimental equipment and large-scale facilities. The University of Tübingen is renowned for its excellence in research and teaching, vibrant student life, and beautiful surroundings. Applicants should hold a Master’s degree in physics or chemistry (or equivalent), demonstrate interest in materials science, possess good written and spoken English, and be able to work both independently and as part of a team. Programming skills (especially Python) and laboratory experience are strong advantages. While knowledge of German is not required, it is considered a plus. The university encourages applications from women and individuals with disabilities, and is committed to equal opportunities and diversity. The position is funded at E13 TV-L, 65% for three years, with employment managed by the university’s central administration. Applications should include a cover letter, CV, and transcript of records, submitted as a single PDF to [email protected]. The application deadline is 28 February 2026. For further details on the group’s research activities and publications, visit the group website .

5 months ago

Publisher
source

Frank Schreiber

University Name
.

University of Tübingen

PhD Student in Physics of Molecular and Biological Matter: Machine Learning for X-ray and Neutron Scattering Data Analysis

The Physics of Molecular and Biological Matter group at the University of Tübingen, led by Prof. Dr. Dr. h.c. Frank Schreiber, is seeking a highly motivated PhD student to join their interdisciplinary research team. The group specializes in the study of molecular and biological matter using advanced X-ray and neutron scattering techniques, with a strong focus on developing machine learning (ML) approaches for efficient data analysis. This position offers the opportunity to contribute to cutting-edge research at the intersection of physics, chemistry, computer science, and materials science. The successful candidate will work on the development of ML-based tools to analyze data from surface sensitive scattering techniques such as X-ray Reflectivity (XRR) and Grazing-Incidence Wide-Angle X-ray Scattering (GIWAXS). Responsibilities include supporting data and metadata formats, integrating software into computational environments, and presenting scientific results at conferences and in publications. The role involves both independent research and collaboration with experienced scientists, particularly during measurement campaigns at synchrotron and neutron facilities. Applicants should hold a Master's degree in physics, chemistry, computer science, or a related field, and demonstrate a strong interest in physics and machine learning. Proficiency in Python and familiarity with ML frameworks like PyTorch or JAX are highly desirable. Good communication skills, motivation to learn new topics, and the ability to work both independently and in a team are essential. While German language skills are not required, they are considered an advantage. The position is funded at the E13 TV-L, 65% level for three years and is integrated into large national and European research consortia, including the DAPHNE NFDI consortium. The group offers access to well-equipped laboratories, a collaborative international environment, and membership in the Cluster of Excellence "Machine Learning: New Perspectives for Science" funded by the DFG. Students benefit from excellent training, supervision, and opportunities to conduct research at major international facilities. The University of Tübingen is recognized as one of Germany's Universities of Excellence, with a rich academic tradition and a vibrant student life. The university is committed to equal opportunities and diversity, encouraging applications from women and disabled candidates. The position is available immediately, with an application deadline of February 28, 2026. For more information about the group and research activities, visit the group website . To apply, prepare a cover letter, CV, and transcript of records, and submit them as a single PDF file to the provided email address. For the official job advertisement and application details, see the university careers page .

5 months ago

Publisher
source

Frank Schreiber

University Name
.

University of Tübingen

PhD Student in Physics of Molecular and Biological Matter – Machine Learning for X-ray and Neutron Scattering Data Analysis

The Physics of Molecular and Biological Matter group at the University of Tübingen, led by Prof. Dr. Dr. h.c. Frank Schreiber, is seeking a motivated PhD student to join their interdisciplinary research team. The group specializes in the physics of molecular and biological matter, employing advanced X-ray and neutron scattering techniques. A key focus is the development and application of machine learning (ML) strategies for efficient analysis of large datasets generated from scattering experiments. This position offers a unique opportunity to contribute to cutting-edge research at the intersection of physics, chemistry, and computer science. The successful candidate will develop ML-based tools for analyzing data from surface sensitive scattering techniques such as X-ray Reflectivity (XRR) and Grazing-Incidence Wide-Angle X-ray Scattering (GIWAXS). Responsibilities include supporting data and metadata formats, integrating software into computational environments, and presenting scientific results at conferences and in publications. The group is part of the Institute of Applied Physics and collaborates with large national and European research consortia, including the DAPHNE NFDI consortium. Students benefit from well-equipped laboratories, a highly collaborative international environment, and membership in the DFG-funded Cluster of Excellence "Machine Learning: New Perspectives for Science." Research activities may involve participation in measurement campaigns at synchrotron and neutron facilities, providing practical experience and opportunities for professional development. Applicants should hold a Master’s degree in physics, chemistry, computer science, or a related field. Essential qualifications include strong interest in physics and machine learning, good written and spoken English, and the ability to work both independently and collaboratively. Programming skills in Python and familiarity with ML frameworks such as PyTorch or JAX are highly advantageous. Experience with surface sensitive scattering techniques and knowledge of German are considered pluses. The University of Tübingen is renowned for its academic excellence, vibrant student life, and commitment to equal opportunities and diversity. The position is funded at E13 TV-L, 50-75% for three years, with access to international research facilities and excellent training and supervision. Applications should include a cover letter, CV, and transcript of records, submitted as a single PDF file to [email protected]. The application deadline is 31.07.2026, and the position is available immediately. For further information about the group and research activities, visit www.soft-matter.uni-tuebingen.de . For details on the application process, see the official job advertisement at this link .

just-published

Publisher
source

Frank Schreiber

University Name
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University of Tübingen

Post-doctoral position: X-ray and Neutron Scattering Techniques in Soft Matter

The Institute of Applied Physics at the University of Tübingen is seeking a post-doctoral researcher to join the research group of Prof. Dr. Dr. h.c. Frank Schreiber . The project focuses on the physics of molecular and biological matter, with an emphasis on X-ray and neutron scattering to investigate the structure and dynamics of soft matter systems . The successful candidate will contribute to the development of scattering methods for studying proteins in solution and related soft-matter samples. The role involves preparing and participating in experiments at major international large-scale facilities, including neutron sources such as ILL in Grenoble and ESS in Lund , and X-ray facilities such as PETRA III , EuXFEL in Hamburg, and ESRF in Grenoble. A further part of the work is the analysis of experimental data, ideally in connection with machine-learning-based tools developed by the group. In addition to research, the postdoc will present results at conferences and in publications, and will also supervise PhD, master’s, and bachelor’s students . The group environment is described as international, collaborative, and well equipped, with opportunities to test new research ideas using the group’s laboratory infrastructure and access to advanced experimental platforms. The position is based at the Institute of Applied Physics in Tübingen, Germany, and is a full-time temporary postdoctoral appointment . The advertised start date is 1 September 2026 , though the text also states the position is to be filled immediately. The application deadline is 31 October 2026 . Applicants should hold a PhD in physics or chemistry, or an equivalent degree , and are expected to have an excellent academic record. Experience with X-ray/neutron scattering techniques such as SAXS , SANS , and XPCS is an advantage. Strong written and spoken English is required, while German is optional but beneficial. Programming experience, especially in Python , practical laboratory skills, good communication, and the ability to work independently and collaboratively are all valued. To apply, candidates must submit a single PDF containing a cover letter, CV, and transcript of records to [email protected] . More information about the research group is available on the group website.

just-published