We are looking for talented machine learning researchers to join our Berlin-based machine learning research team. Our various academic programs cater to multiple levels of expertise and include a wide range of research focus areas:
- Learning with Minimal Supervision (Weakly-supervised / Semi-supervised / Self-supervised / Unsupervised learning)
- Vision and Language (Image Captioning, VQA, Visual Dialogue)
- Few-shot Learning
- Privacy / Security / Fairness in Machine Learning
- Interpretable / Explainable Machine Learning
- Efficient Deep Learning
- Domain Adaptation
- Lifelong Learning
If you are interested in working within an industrial research team and exploring various machine learning research areas and its relevance and applicability in an industrial context, check out the below opportunities!
Master Thesis Program
Our six-month master’s thesis program is designed for young talents who are interested in gaining hands-on experience in working as part of an industrial research team. As a master’s thesis student, you will have the opportunity to write your master’s thesis in one of our research areas, be mentored by an international team of experienced researchers and data scientists and gain valuable exposure to various real-world machine learning challenges posed by SAP customers and different SAP product units.
Ph.D. Internship Program
Our 3 to 6-month Ph.D. internship program is designed for Ph.D. students in their 2nd year (or later) with an interest in gaining expertise and publishing in one of our research areas. We accept applications from Ph.D. students with at least one publication in a top machine learning conference or journal.
As a Ph.D. intern, you will have the opportunity to gain valuable hands-on experience in machine learning industrial research. You will have the chance to work with rich datasets and real-world issues, and you will work in close collaboration with our research partners from top universities worldwide, such as the University of Amsterdam, MIT, Cornell University, University of Pittsburgh, to name a few. You will also supervise Master Thesis students towards publishing research papers at top machine learning conferences and journals.
Visiting Scholar Program
Our 3 to 6-month visiting scholar program is designed for post-doc researchers with a Ph.D. degree in one of our research areas, in-depth expertise in machine learning and deep learning research, and an established track record of publications in top machine learning conferences and journals.
As a visiting scholar, you will have the opportunity to shape existing research areas and establish new ones within the context of machine learning industrial research at SAP. You will have the chance to combine academic freedom with access to rich datasets, and business use-cases posed by SAP product teams and SAP customers. You will be able to assume responsibility and set the agenda for a team of Ph.D. and master students working at SAP Machine Learning Research.
How to Apply
Interested in applying to one of our programs? Send us an email at email@example.com highlighting your research interests and your published work.
Please note that, in compliance with EU data protection regulations, we do not accept applications or CVs via e-mail. We will reach out to qualified candidates with specific instructions for next steps involving the official SAP online application platform.
We are looking forward to hearing from you!
About SAP Leonardo Machine Learning Research
At SAP Leonardo Machine Learning Research, we are the interface between academia and industry. Our interdisciplinary research projects are guided by the intersection between academic research working on key challenges and trends in the machine learning field and use cases from SAP customers and different SAP product units.
By partnering with a global academic network of top-tier universities and research institutes, we work on pushing the state of the art in machine learning fields that are relevant to SAP enterprise solutions. Outcomes of our research projects make our enterprise solutions more efficient, scalable, interpretable, private, and secure.