Postdoc in Distributed Systems / Data Science Systems
Kungliga Tekniska högskolan, Skolan för elektroteknik och datavetenskap
The division of Software and Computer Systems at the Department of Computer Science, KTH, is looking for excellent candidates for two postdoctoral positions in the area that lies at the intersection of distributed systems, data science, data intensive computing, machine learning and deep learning. The selected candidates are expected to have a strong background and passionate interest in topics of at least two of aforementioned areas.
The advertised postdoctoral positions are mainly within the following two projects: (1) Horizon 2020 EU-Project ExtremeEarth: From Copernicus Big Data to Extreme Earth Analytics ( http://earthanalytics.eu/ ) that aims at developing scalable Extreme Earth Analytics techniques and technologies for extracting information and knowledge out of the petabytes of Copernicus data collected in the European Copernicus program for monitoring the Earth; (2) CDA: Continuous Deep Analytics that aims at development of the foundations for data programming systems following two main avenues of research: (i) Algorithms, programming Languages and optimization for continuous analytics on data streams such as time-varying relational models, linear algebra and dynamic graphs ; (ii) Distributed Runtime for complex and fast hardware-accelerated (GPUs, FPGAs) as well as data-parallel processing on data streams with large state.
Within the ExtremeEarth: From Copernicus Big Data to Extreme Earth Analytics project, one postdoc, together with PhD students from KTH and researchers from RISE SICS, and Logical Clocks AB, will contribute to development of novel and enhancement of existing techniques, methods and algorithms for scalable big data analysis, as well as to building and enhancing a platform for Data Science and Data Engineering, such as Hopsworks, in order to provide system support for scalable big data analytics and to offer unprecedented scalability to extreme data volumes and scale-out distributed deep learning for Copernicus data.
Within the CDA: Continuous Deep Analytics project, the second postdoc will join a strong team of senior researchers, PhD students and research engineers in software systems in order to contribute to the fundamental design and development of next-generation open-source software for data analytics. As a member of the CDA team, the postdoc is expected to acquire deeper knowledge in distributed system technology, grasp fundamental problems and learn to find elegant solutions as well as putting into use and evolving further programming skills and background in data management, ML or programming languages. The group has regular discussion meetings and frequent interactions with other leading universities as well as a clear vision and high publication quality, aiming only for top-tier venues in the field (e.g., USENIX, VLDB, SIGMOD, PLDI).
Applicants must hold or be about to receive a doctoral degree in Computer Science (or equivalent). The doctoral degree must have been obtained within the last three years from the application deadline (some exceptions for special grounds, for instance sick leave and parental leave). The candidate should have a strong background from at least two of the areas distributed systems, data science, data intensive computing, machine learning and deep learning. The successful applicant should have an outstanding research and publication record in at least two of the aforementioned research areas as well as experience in developing systems and applications. Strong skills in modern Machine Learning and data-intensive computing frameworks (e.g., TensorFlow, Keras, Apache Spark, Apache Flink) is a requirement. Track record in contributing to Open-Source is a plus. Well-developed analytical and problem solving skills are a requirement. We are looking for a strongly motivated person, who is able to work independently as well as in an international research team. The applicant should have a well-established international research collaboration network as should be indicated by visits, guest talks or internships outside applicant s home institutions. The applicant should also have a track record in being a reviewer of reputed international conferences or journals. Good command of English orally and in writing is required to present and publish research results.
Great emphasis will be placed on personal competence and suitability.
Trade union representatives
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The application should contain the following:
- CV including relevant professional experience and knowledge.
- Copies of diplomas and grades from your previous university studies. Translations to English or Swedish if the original documents are not issued in one of these languages.
- A research statement on why you want to conduct research in areas of Distributed and Data Science Systems, about your academic interests and how they relate to your previous studies and future goals; max 2 pages long.
- Representative publications or technical reports: Document no more than 10 pages each. For longer documents (eg dissertations), attach a summary (abstract) and a web link to the full text.
- Two recommendation letters
- Contact information for two reference persons. We reserve the right to contact references only for selected candidates.
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Your complete application must be received at KTH no later than the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time).
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Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.
Type of employment: Temporary position longer than 6 months
Working hours: Full time
Salary: Monthly salary
Reference number: J-2019-1192
Last application date: 2019-06-30
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