Postdoctoral Fellow in Distributed Systems / Systems for Data Analysis

Royal Institute of Technology

Sweden

 

Duties

The Department of Software and Computer Systems at the Department of Computer Science, KTH, is looking for excellent candidates for two postdoctoral services in the area in the intersection of distributed systems, computer science, data-intensive data processing, machine learning and deep learning. The selected candidates are expected to have a strong background and passionate interest in at least two of the above mentioned areas.

The postdoctoral services announced mainly concern the following two projects: (1) Horizon 2020 EU project "ExtremeEarth: From Copernicus Big Data to Extreme Earth data analysis" ( http://earthanalytics.eu/) which aims to develop scalable techniques in Extreme Earth and techniques to extract information and knowledge from the petabytes of Copernicus data collected in the European Earth monitoring program Copernicus, (2) "CDA: Continuous Deep Analytics" which aims to develop the foundation of computer programming systems that follow two main areas of research: (i) Algorithms, programming languages and optimization for continuous analysis of data streams such as time variations, linear algebra and dynamic graphs; (ii) Distributed Runtime for complex and fast hardware accelerated (GPU, FPGA) and data-parallel processing of large-state data streams.

Within the project "ExtremeEarth: From Copernicus Big Data to Extreme Earth Analytics", a postdoctoral fellow with PhD students from KTH and researchers from RISE SICS and Logical Clocks AB will contribute to the development of new and improved existing techniques and methods, algorithms for scalable analysis of large data sets as well as building and improving a data analytics and data processing platform, such as Hopsworks, to provide system support for scalable big data analytics and offer unparalleled scalability for extreme data sets and scaled distributed deep learning for Copernicus data.

Within the project "CDA: Continuous Deep Analytics", the second postdoc will join a strong team of senior researchers, doctoral students and research engineers in software systems to contribute to the basic design and development of the next generation open source software for data analysis. As a member of the CDA team, postdoc is expected: to acquire deeper knowledge of technology for distributed systems, understand basic problems and learn to find elegant solutions, and use and develop additional programming skills and backgrounds in data management, ML or programming languages. The group has regular discussion meetings and frequent interaction with other leading universities as well as a clear vision and high publication quality, which is only aimed at the leading forums in the field (eg USENIX, VLDB, SIGMOD, PLDI). 


Qualifications

The applicant must have completed a doctorate or be close to a doctorate in computer science or equivalent. The doctoral degree must have been completed no more than three years before the last application date. Applicants should have a strong background in at least two of the following areas: distributed systems, data analysis systems, data-intensive computations, machine learning and deep learning. A successful applicant must have an exceptional research and publication history in at least two of the above-mentioned research areas, as well as experience in developing systems and applications. Strong skills in modern machine learning and data-intensive computational frameworks (eg, TensorFlow, Keras, Apache Spark, Apache Flink) are required. A history of contributing to Open-Source is a plus.

The selected candidate needs to have an excellent academic track record, well-developed analytical skills, and problem-solving skills. We are looking for a highly motivated candidate who can work independently and in an international research network. The applicant must have a well-established international research network, which must be documented through visits, guest lectures or internships outside the applicant's home institution. The applicant must also have documented to have been an assessor for reputable international conferences or journals. Good knowledge of English in speech and writing is necessary to publish and present research results in international conferences and journals.

We will place great emphasis on personal fitness.

Trade union representatives

You will find contact information for union representatives on KTH's website . 


Application

The application must contain the following:

  1. CV including relevant professional experience and knowledge.
  2. Copies of diplomas and grades from your previous university studies. Translations into English or Swedish if the original documents are not issued in one of these languages. 
  3. A brief account of why you want to conduct research in distributed systems / systems for data analysis, about your academic interests and how these relate to your past studies and future goals; max 2 pages long.
  4. Representative publications or technical reports: Documents no longer than 10 pages each. For longer documents (eg dissertations), attach an abstract and a web link to the full text.
  5. Two letters of recommendation
  6. Contact information for two reference persons. We reserve the right to contact references only for selected candidates.

You apply through KTH's recruitment system. As an applicant, you have the main responsibility for your application being complete when it is submitted.

The application must be submitted to KTH by the latest application date at midnight, CET / CEST (Central

European Time / Central European Summer Time). 


Other

Gender equality, diversity and distance from all forms of discrimination are both a quality issue and an obvious part of KTH's core values.

For information on the processing of personal data in connection with recruitment, read more here.


In your application, please refer to Professorpositions.com

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