EURAXESS Czech Republic
Open PhD Position on Edge AI for Accelerator Physics
EURAXESS Czech Republic, Germantown, Ohio, United States
Organisation/Company Hamburg University of Technology Department Computer Science Research Field Computer science » Computer systems Computer science » Programming Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Germany Application Deadline 31 Oct 2025 - 23:59 (Europe/Berlin) Type of Contract Temporary Job Status Full-time Hours Per Week 39 Offer Starting Date 1 Mar 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
Offer Description Artificial Intelligence for Enhancing Operation and Exploitation of X-ray Free-Electron Lasers (AIOPs4XFEL)
Modern X-ray free-electron lasers (XFELs) have transformed how scientists study molecular and material structures. Their unique beam properties are crucial for experiments, but optimizing these features, especially advanced ones such as the wavefront shape, is a complex and time-consuming endeavor. Moreover, the lack of near-real-time feedback from experiments to the XFEL machine prevents immediate beam adjustments, resulting in inefficient use of valuable experimental time and limiting XFEL's full scientific potential.
In this project, AI4Ops@XFEL, we propose optimizing X-ray free-electron laser (XFEL) operation through AI-driven real-time feedback, addressing critical challenges in optimizing beam parameters and maximizing data quality. By integrating machine learning into experimental diagnostics, this project aims to unlock AI-based control over XFEL beam properties, building the foundation for significantly enhancing experiment quality.
Requirements
Master's degree (or equivalent) in computer science (or a closely related degree program) with a grade of “good” or better according to the German or ECTS grading scale
Expertise in deep learning, modern DNN architecture such as attention and transformers, and/or reinforcement learning
Expertise in Efficient ML, Edge AI and/or TinyML
Background (or strong interests) in physics, especially quantum mechanics, particle physics, and accelerator physics
Position Hamburg University of Technology 100% EGR. 13 (TVöD) position for three years
Deadline October 31, 2025
The TUHH values diversity, therefore all applications are welcome, regardless of gender, gender identity, ethnic origin, nationality, age, religion and belief, disability, sexual orientation and identity or social background. The TUHH stands for equal opportunities as well as appreciative and respectful cooperation.
Details and applications: https://www.dashh.org/application/phd_topics/aiops4xfel/index_eng.html
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Offer Description Artificial Intelligence for Enhancing Operation and Exploitation of X-ray Free-Electron Lasers (AIOPs4XFEL)
Modern X-ray free-electron lasers (XFELs) have transformed how scientists study molecular and material structures. Their unique beam properties are crucial for experiments, but optimizing these features, especially advanced ones such as the wavefront shape, is a complex and time-consuming endeavor. Moreover, the lack of near-real-time feedback from experiments to the XFEL machine prevents immediate beam adjustments, resulting in inefficient use of valuable experimental time and limiting XFEL's full scientific potential.
In this project, AI4Ops@XFEL, we propose optimizing X-ray free-electron laser (XFEL) operation through AI-driven real-time feedback, addressing critical challenges in optimizing beam parameters and maximizing data quality. By integrating machine learning into experimental diagnostics, this project aims to unlock AI-based control over XFEL beam properties, building the foundation for significantly enhancing experiment quality.
Requirements
Master's degree (or equivalent) in computer science (or a closely related degree program) with a grade of “good” or better according to the German or ECTS grading scale
Expertise in deep learning, modern DNN architecture such as attention and transformers, and/or reinforcement learning
Expertise in Efficient ML, Edge AI and/or TinyML
Background (or strong interests) in physics, especially quantum mechanics, particle physics, and accelerator physics
Position Hamburg University of Technology 100% EGR. 13 (TVöD) position for three years
Deadline October 31, 2025
The TUHH values diversity, therefore all applications are welcome, regardless of gender, gender identity, ethnic origin, nationality, age, religion and belief, disability, sexual orientation and identity or social background. The TUHH stands for equal opportunities as well as appreciative and respectful cooperation.
Details and applications: https://www.dashh.org/application/phd_topics/aiops4xfel/index_eng.html
#J-18808-Ljbffr