Postdoctoral Fellow in Machine Learning for Physics and Meta-Learning (m/f/d)

Constructor University (formerly Jacobs University) is a private, state-accredited, English-language university in Bremen. We offer Bachelor, Master, and PhD programs in three schools: School of Science, School of Computer Science and Engineering, and School of Business, Social and Decision Sciences. Our principles are first-class teaching and research, international diversity, and transdisciplinary cooperation. According to the 2024 Times Higher Education (THE) World University Rankings, Constructor University is among the top 25 percent out of more than 1900 universities worldwide and is ranked as the second most international university in the world. As an international university, we attract highly talented and open-minded students from all over the world. Currently, over 1,600 students from 110 nations live and study on our residential campus.

Your responsibilities:  

• Develop stochastic optimization methodologies tailored for high-energy physics applications, particularly for the SHiP experiment, a project focused on detecting hidden particles.
• Optimize the geometry of particle detectors using stochastic surrogate models, enabling precise particle tracking.
• Conduct research on meta-learning methods, with applications in diverse fields like tabular data analysis.
• Prepare and publish research articles in top-tier journals and conferences (e.g., Journal of Instrumentation, JMLR, NeurIPS), and contribute to project reporting. 
• Collaborate on and actively contribute to research grant applications to secure additional funding for future projects.

Your qualifications:  

• PhD in machine learning, physics, computer science, or a related field with experience in stochastic optimization and computational modeling.
• Strong background in surrogate modeling, gradient estimation, and stochastic methods.
• Experience with meta-learning techniques, especially hyper-networks, Deep Sets, or Transformer architectures, and a working knowledge of decision tree algorithms in machine learning.
• Proven ability to contribute to grant writing and experience in preparing competitive research proposals.
• Excellent programming skills and a track record of published research in relevant journals and conferences. 

What you can expect at Constructor University: 

Constructor University is dedicated to equal opportunity employment and

invites applications from individuals of all backgrounds, irrespective of gender identity, gender expression, age, physical characteristics, disability, nationality, ethnic and cultural backgrounds, social and political affiliations, religion, family status, pregnancy, or sexual orientation. We are committed to ensuring fair

treatment for all applicants and preventing any form of discrimination.

Constructor University actively encourages applications from women and

minority groups. Particularly, we invite candidates with extensive international experience to apply, aiming to further enrich the diversity of our faculty. 

Constructor University consistently achieves top results in national and

international university rankings. 

In the CHE Ranking, the most comprehensive and detailed ranking of the

German-speaking higher education landscape, Constructor University has

achieved top placements every year since its first participation in 2005. 

Your application:   

For any further information regarding this position, please contact

Dörte Etzrodt (Senior HR Business Partner), via Mail (detzrodt@constructor.university) or job-application@constructor.university. 

Apply today - it's simple and uncomplicated. We look forward to getting to know you.  

The review of applications will begin immediately. Please note that only applications submitted through the official application portal will be considered for recognition.