3 PhD: Marie-Curie DN RELAX: distributed/parallel/stream data analytics

The PhD students will join a high-profile group of researchers working on parallel and distributed data processing, the Chalmers Distributed Computing and Systems group. The positions offer an opportunity to work in the area of designing, analyzing and applying cutting-edge methods for key problems in parallel, distributed and streaming data processing in the context of data analysis. The software systems that support data analytics operate under stringent constraints for response times, throughput, scalability, and availability. By focusing on scalable, parallel, structural data sharing, we target principled data analysis and processing mechanisms that fulfill scalability and latency requirements on ML computations and data processing for critical use-cases.

Major responsibilities
The core of the research will be on the design and implementation of continuous /streaming data processing algorithms and system components, that allow for efficient parallel, distributed and adaptive data analysis with configurable guarantees, balancing accuracy and efficiency trade-offs where applicable, considering many-core and distributed architectures and leveraging their underlying parallelism. Example targets include: enabling data analytics models for incremental (stream) processing and bulk-iterative workloads operating in unison; algorithmic constructs and data structures to maintain synopses supporting concurrent updates and queries in varying window frames; methods to trade staleness of state for gaining performance without loss in accuracy in deep learning and iterative large data processing algorithms.

The PhD students will join RELAX (www.relax-dn.eu), our ambitious Marie Skłodowska-Curie Doctoral Network, financed by the EU commission and supported by European industry actors; the list of collaborating partners includes Trinity College Dublin, Queen's Un. Belfast, National Technical Un. of Athens, Aarhus Un.
The RELAX European Doctoral Network aims to train a cohort of highly mobile and adaptable researchers to become experts in the design of scalable and efficient data-intensive software systems. These experts will master the specific skill of navigating the semantics or correctness conditions of applications, with the goal of enhancing scalability, response times, and availability. Working across the disciplinary specialisms of data science, data management, distributed computing and computing systems, the Fellows will develop knowledge of the broad issues underpinning data analytics systems.

The 3 PhD students will be supervised by Vincenzo Gulisano, Marina Papatriantafilou and Philippas Tsigas, respectively. They have successfully supervised to completion more than 20 PhDs, with followup career steps at institutes including MPI for Computer Science, Ericsson Research, Volvo R&D, and Universities incl. Darmstadt, EPFL, Maryland, Purdue, Stuttgart.

As a PhD student you are expected to develop your own scientific concepts and communicate the results of your research verbally and in writing.

Qualifications
To qualify as a PhD student, you must have a solid background in Computer Science and Engineering or in a related discipline, corresponding to a master's level degree of at least 240 higher education credits by the starting date. You have genuine interest and curiosity in the subject matter, you are highly motivated, self-propelled, energetic, independent and with a well-developed analytical problem-solving ability. As a person, you are empathetic, loyal and have high ethical standards. Your communication skills in English (written and oral) are of a high quality. If Swedish is not your native language, Chalmers offers Swedish courses. Both Swedish and English are used in undergraduate courses. The ideal candidates for the positions have a strong background in distributed/parallel/stream computing and systems, including both algorithmic aspects and programming. Scientific excellence and successful synergies are very important. Further experience with interdisciplinary projects or background in cyber-physical systems, data analysis is helpful.

Contract terms
Full-time temporary employment. The position is limited to a maximum of five years.

We offer
Chalmers offers a cultivating and inspiring working environment in the coastal city of Gothenburg. 
Read more about working at Chalmers and our benefits for employees.

The alumni of MSCA-DNs have formed a vibrant community. Check their website:  https://www.mariecuriealumni.eu/ for more information on the benefits of being part of a  MSCA-DN.

Application procedure
The application should be marked with Ref 20230221 and written in English. The application should be sent electronically and be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.

CV: (Please name the document: CV, Family name, Ref. number)
• CV
• Motivation letter: (Please name the document as: Motivation letter, Family name, Ref. number) 1-3 pages where you: introduce yourself, describe your previous experience of relevance for the position (e.g. education, thesis work and, if applicable, any other research activities), your future goals and future research focus in connection to this positions.
• Two references that we can contact.

Other documents:
• Copies of bachelor and/or master’s thesis.
• Attested copies and transcripts of completed education, grades and other certificates, e.g. TOEFL test results.
• Evidence of written work: (links to) research papers or other reports.
• Links to software repositories with relevant projects.
It is important to include parts of your own work such as theses and articles that you have authored or co-authored. Please notice also that it is highly recommended that you include letters of recommendation; we typically get a large number of applications, and it is not feasible for us to request individual letters.

Please use the button at the foot of the page to reach the application form. 

Application deadline: 7 May 2023

For questions, please contact:
Philippas Tsigas, tsigas@chalmers.se, 031-7725409
VIncenzo Gulisano, vincenzo.gulisano@chalmers.se, 031-7726147
Marina Papatriantafilou, ptrianta@chalmers.se, 031-7725413

*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***