The research group "Enterprise Platform and Integration Concepts" (EPIC) offers a unique possibility for graduate and under-graduate student level research in an international and multi-disciplinary setup. Our research projects are driven by real-world software engineering challenges and usually stem directly from our industry partners we are working with.

• Research Assistant and PhD student for In-Memory and Cloud-Based Enterprise Data Management
• Research Assistant and PhD student at EPIC
• PhD Scholarships at EPIC and the HPI Research School

If you are interested in our research group and its topics, we are open for speculative applications. We expect prospective PhD candidates to apply with an exceptional Master's degree in computer science (or equivalent) and also show a strong record of project and outstanding team work. Please send your application including a cover letter and your CV to office-epic(at)hpi.de. If you have any questions, feel free to reach out Dr. Michael Perscheid.

In HPI's Masters program, we are looking for students with both exceptional grades and experience in software development in order to drive projects with our industry partners. Prospective students should have a strong interest in working on applied computer science problems directly with our partners. This particular approach to project work supports students in building relationships with potential employers: many of our previous project student assignments have led to (international) internships and job offers. Project students are welcome to engage in any of the following activities:

• HYRISE HYRISE is an open-source hybrid row/column in-memory database engine written in C++. If you are interested to contribute to this project or to perform measurements and experiments in the context of in-memory data management research, please contact Markus Dreseler or Jan Kossmann.

• Real-Time Stream Processing The area of real-time data stream processing is becoming more important in the light of developments towards trends like Internet of Things (IoT). In that context, we aim to compare different systems and concepts, which can include research in the area of performance benchmarks. If you are interested in this topic or similar ones, please contact Guenter Hesse.
• Data-Driven Causal Inference Causal structure learning has the intention to estimate the underlying causal graphical model from observational data. In our research, we address open challenges in this field by improvements in both the application of statistical and probabilistic concepts, and the efficient implememtation of algorithms using modern hardware, e.g., GPUs. Our goal is to enable an utilization in a real world context. If you are interested in this topic, please contact Johannes Huegle or Christopher Hagedorn.
• Data-Driven Decision-Making and Optimal Control The need for automated data-driven decision-making is everywhere and becomes increasingly important. In our research, we seek to derive automated decision-support using quantitative methods of operations research and data science applied in the areas of (i) operations management and (ii) database optimization. Please contact Dr. Rainer Schlosser.

For more information about our ongoing projects, have a look at our projects website. We are able to compensate students on an individual basis depending on experience and the particular industry project they will be working on. Please contact Dr. Michael Perscheid for details.

We have open positions for motivated student assistants (HiWis) to support our activities in the following areas:

• Main-memory based applications / architectures
• Real-time stream processing / Internet of Things (IoT) applications / architectures 
• IT infrastructure and lab administration
• Human-centered software design, user research
• General activities of the research group

What we are looking for:

• Interest in our research, new applications, software design, performance
• Ability to learn and apply new technologies
• Motivation, willingness to become a reliable team member

If you are interested please visit us in the Villa on Campus II or contact Dr. Michael Perscheid.