Assistant Professorship tenure track in BioImaging and Data Analysis

We are seeking candidates in the field of bioimage analysis, computer vision, and machine learning who work at the forefront of developing and applying quantitative spatially and/or temporally resolved approaches to study biological phenomena across multiple scales. For this position, the focus lies on candidates who apply computational methods to extract multi-scale information from bioimage datasets and use this to make fundamental discoveries in cell and developmental biology. This can range from, but is not limited to, theoretical approaches to extract information from noisy or undersampled imaging signals, deep learning-aided methods for image restoration, segmentation, and feature extraction, to statistical methods that capture and connect multivariate information across spatial and temporal scales, and multi-scale simulations.

The successful candidate must be an early career researcher in the field of bioimage analysis with a proven track record in terms of research output and optimally experience in acquisition of third-party funding, and teaching and mentoring. Although emphasis lies on computation, having experience in experimental cell and developmental biology and multiscale/multiplex imaging will be an advantage. The future professor is expected to strengthen the scientific impact and societal role of the Department of Molecular Life Sciences (DMLS), to become an integral member of the recently founded BioVisionCenter (BVC) at the University of Zurich (UZH), and to contribute to the mission of the BVC to provide access to advanced bioimage analysis methods at scale. The professor will also contribute to the teaching mission of the BVC and its further development at both Bachelor and Master level, in particular with courses on bioimage analysis, machine learning, and data-driven modelling, and supervise PhD students.

UZH sees scientists as modern leaders who conduct excellent research - taking into account the Open Science principles - through their own research projects as well as the promotion of excellent junior researchers, and who help to shape a future-oriented University with innovative research-based teaching. Situated in the open-minded and family-friendly city of Zurich, which combines the vibrant cultural scene in a modern European city with the convenient accessibility to its beautiful natural surroundings, UZH is well integrated in the city's community and research environment.

UZH provides generous research support, including dedicated funds for personnel, running expenses, and competitive start-up packages. Additionally, the successful applicant is expected to acquire external research funding. Zurich's scientific environment encompasses a rich spectrum of diverse activities.

The employment conditions for this position follow UZH's legal regulations and include part-time options. UZH is an equal-opportunities employer, and the Faculty of Science, in particular, strives to increase the percentage of women and underrepresented groups in leading positions. Therefore, qualified female researchers are particularly encouraged to apply. Care-time interruptions are considered during the evaluation of applicants of all genders.

Assistant Professorship tenure track in BioImaging and Data Analysis

Applicants are kindly invited to submit their applications, which should include:

• a cover letter (max. 1 page)
• a Curriculum Vitae with date of submission, including teaching and supervisory track record; outreach activities; a list of acquired competitive funding, including role and amount award-ed to the candidate
• a description of their research outputs relevant for this application and their importance for the field (at most five outputs, max. 1 page in total)
• a research plan describing their mid-term scientific strategy and expected impact (max. 2 pages)
• a teaching reflection on their educational values, tools and methods, and their potential contribution to the curriculum development at UZH (max. 1 page)
• a description of their track record and/or planned measures towards diversity, equality, inclusion, and sustainability (max. 0.5 page)
• a list of publications and other research outputs, including dataset, code, etc.
• a copy of their PhD certificate

Please note that page limitations do not include references.

The evaluation processes at UZH and its Faculty of Science follow the DORA recommendations for assessing research quality and impact. Applicants are thus asked to refrain from referring to non-personal measures such as impact factors.

For further information, please contact E-Mail schreiben.