Marco Stampanoni

ETH Zurich is recruiting a Postdoctoral Fellow / Process Engineer for metal assisted chemical etching within the X-ray Imaging Professorship. The position sits at the intersection of advanced micro- and nanofabrication, X-ray optics, and translational imaging research, with a strong focus on improving the fabrication of high-aspect-ratio silicon microstructures for next-generation X-ray imaging applications. The successful candidate will join the SNSF-funded ABSOLUTE project, which develops an innovative catalyst concept for defect control in metal-assisted chemical etching (MacEtch) of silicon. The project addresses key challenges in process reliability, scalability, defect reduction, and manufacturing quality, with direct relevance to the clinical translation of grating-based X-ray interferometry. Work will be carried out in a multidisciplinary environment in collaboration with academic and industrial partners, under the supervision of Prof. Dr. Marco Stampanoni and Dr. Lucia Romano , with project-related supervision at the Paul Scherrer Institute. The role is highly practical and research-intensive. Responsibilities include expanding MacEtch testing capabilities across different feature sizes and aspect ratios; investigating defect formation mechanisms; optimizing process parameters; assessing scalability; and contributing to robust fabrication workflows for complex silicon microstructures. The researcher will fabricate and process 4-inch silicon wafers using UV photolithography, thin-film deposition, thermal treatments, and MacEtch, and will perform characterization using optical microscopy, SEM, and profilometry. Additional tasks include documenting experiments carefully, analyzing data, preparing technical reports, contributing to deliverables, presenting at conferences and workshops, and publishing results in high-impact journals. Applicants should hold a PhD in Physics, Chemistry, Materials Science, Engineering, or a closely related field. Strong cleanroom experience and practical knowledge of semiconductor processing are required, along with hands-on expertise in photolithography and SEM. Experience with silicon etching and MEMS fabrication is especially desirable. The post calls for strong analytical skills, a collaborative mindset, excellent communication in English, and the ability to work effectively in a project-driven, multidisciplinary setting. Willingness to travel within Europe for up to 20% of working time is also expected. The appointment is initially for one year, with the possibility of extension. ETH Zurich emphasizes interdisciplinary collaboration, innovation, diversity, sustainability, and a supportive working environment with on-the-job training and professional development opportunities. The application must be submitted via ETH Zurich's online portal, and applicants should include a motivation letter, CV, publication list, transcripts, and at least two reference letters. Applications by email or post will not be considered.

ETH Zürich is offering a doctoral position in sparse reconstruction of virtual histology images within the X-ray Imaging Professorship and its translational imaging environment at the Paul Scherrer Institute (PSI). The project sits at the intersection of synchrotron-based imaging, machine learning, and medical translation, with a strong focus on improving histopathological assessment of tumor biopsies and supporting better outcomes for oncological patients. The successful doctoral researcher will contribute to the design and implementation of machine-learning-based sparse 3D reconstruction methods for fast virtual histology using X-ray phase-contrast radiography and tomography. The work is embedded in a multidisciplinary team of academic and clinical researchers, with exposure to ongoing pilot studies at cantonal hospitals and opportunities to contribute to clinical workflow improvement in cancer diagnostics. Core research tasks include collecting grating-interferometry X-ray phase-contrast microCT data from breast tissue biopsies, building data pipelines for synchrotron and laboratory microCT scans of soft tissue, and developing reconstruction algorithms for virtual histopathology from sparse phase-contrast CT acquisitions of oncological specimens. The project also includes comparing outputs with standard histology, evaluating algorithm performance, presenting results at conferences and workshops, and publishing scientific results. Applicants should hold a Master’s degree or equivalent in physics, engineering, or computer science. Strong skills in computer vision, machine learning, and Python are expected. Knowledge of X-ray physics and laboratory imaging is considered an advantage. The position also values high motivation, curiosity, strong organization, commitment to collaborative work, and excellent English communication skills. ETH Zürich highlights its culture of interdisciplinary collaboration, innovation, sustainability, and diversity. The role comes with on-the-job training, professional development opportunities, and modern employment conditions in a supportive research environment. Applications must be submitted online and should include a motivation letter, CV, publication list, and transcripts; ideally, candidates should also provide two reference letters. For questions about the position, applicants may contact Prof. Dr. Marco Stampanoni at [email protected] or Dr. Gianluca Lori at [email protected] . The application deadline is not specified in the posting.