Research Associate for model independent searches for new physics with the CMS experiment § 28 Subsection 1 HmbHG

Your responsibilities

Research associates will be expected primarily to teach and conduct research. The research associate will also have the opportunity to pursue further academic qualifications, in particular a doctoral dissertation. At least one-third of set working hours will be made available for the research associate’s own academic work.

Despite an impressive and extensive effort by the LHC collaborations, there currently is no convincing evidence for new particles produced in high-energy collisions. However, it is clear that the Standard Model cannot be the final theory of nature. Recent years have seen a great increase in anomaly-based strategies to search for new physics, such as the weakly-supervised CATHODE approach co-developed in Hamburg.

The successful candidate will further develop and carry out machine-learning based model-independent searches for new particles in proton-proton collision data recorded at the CMS experiment.

Our group consists of more than 60 members and is deeply involved in detector R&D as well as calibration and data analysis of the CMS experiment. Interested candidates will be offered the opportunity of own research, advanced training and development of teaching skills in a stimulating scientific environment.

A close collaboration exists with other research groups in experimental and theoretical physics of the University and of DESY located on the same campus. Our group is part of the Cluster of Excellence “Quantum Universe” which performs research to understand mass and gravity at the interface between quantum physics and cosmology. The research team includes leading scientists from mathematics, particle physics, astrophysics, and cosmology at Universität Hamburg and DESY. Beyond Hamburg, we closely collaborate with other nationally and internationally leading groups on the development of AI techniques for fundamental physics.

The position provides for 2.5 teaching hours per week.

Your profile

A university degree in a relevant field.

Excellent English communication skills are required. Excellent candidates will have prior knowledge of high energy physics as well as practical experience in deep learning methods. Candidates with experience in analyzing proton-proton collision data, anomaly detection methods, or related ML techniques for particle physics are preferred.

Successful candidates are expected to pursue a PhD in Physics at the University of Hamburg. The regular duration of a PhD at the Department of Physics is three years.

We offer

Reliable remuneration based on wage agreements
Continuing education opportunities
University pensions
Attractive location
Flexible working hours
Work-life balance opportunities
Health management

Educational leave

30 days of vacation per annum

Universität Hamburg—University of Excellence is one of the strongest research educational institutions in Germany. Our work in research, teaching, educational and knowledge exchange activities is fostering the next generation of responsible global citizens ready to tackle the global challenges facing us. Our guiding principle “Innovating and Cooperating for a Sustainable Future” drives collaboration with academic and nonacademic partner institutions in the Hamburg Metropolitan Region and around the world. We would like to invite you to be part of our community to work with us in creating sustainable and digital change for a dynamic and pluralist society.

The Free and Hanseatic City of Hamburg promotes equal opportunity. As women are currently underrepresented in this job category at Universität Hamburg according to the evaluation conducted under the Hamburg act on gender equality (Hamburgisches Gleichstellungsgesetz, HambGleiG), we encourage women to apply for this position. Equally qualified and suitable female applicants will receive preference.

Severely disabled and disabled applicants with the same status will receive preference over equally qualified non-disabled applicants.

Back to overview Online application