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Postdoc in Verified, Distributed Data Stream Processing

Københavns Universitet (KU)



Department of Computer Science
Faculty of Science

University of Copenhagen

The postdoc position is part of the research project DISCOVER (Distributed Streaming Computations, Verified) funded by the Independent Research Fund Denmark (DFF).

Today’s software and hardware systems produce massive amounts of data. Stream processing frameworks are vital tools for software engineers and data scientists to tame this data. They provide convenient programming abstractions that allow their users to express the desired data analysis. From the expressed analysis, they generate a distributed program and deploy it on computing clusters, which enables the massively parallel processing of data. Apache Flink, Apache Spark, and Google Cloud Dataflow are examples of mature stream processing frameworks that are widely used in industry. For thousands of users these frameworks serve as both the programming language and the operating system. Yet, these systems exhibit unreliable and unpredictable behavior, which prohibits their use in scenarios that cannot tolerate errors such as data loss. The goal of the position is to contribute to an ongoing formalization effort using the Isabelle proof assistant towards the first formally verified system for the analysis of big data.

Applicants must hold a PhD in computer science or a closely related field. The ideal candidate is an experienced proof assistant user (e.g., of Isabelle), has some experience with reasoning about distributed systems or reasoning by coinduction, and is generally interested in formal methods, logic, and engineering correct software.

The postdoc’s main duty is to carry out research within the scope of DISCOVER and in close collaboration with other project participants. The post may also include performance of other duties, such as undergraduate student (co)supervision.

Further information on the Department can be found at https://di.ku.dk/english/. Inquiries about the position can be made to Dmitriy Traytel, [email protected].

The position is open from 1 January 2025 or as soon as possible thereafter. The position will be filled for two years with a possible extension by another year.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

Terms of employment
The position is covered by the Memorandum on Job Structure for Academic Staff.

Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.

Negotiation for salary supplement is possible.

The application, in English, must be submitted electronically by clicking APPLY NOW below.

Please include

  • Cover letter with a brief motivation statement
  • Curriculum vitae
  • Diplomas (Bachelor, Master and PhD degree or equivalent)
  • Complete publication list
  • Separate reprints of 3 particularly relevant papers

The deadline for applications is 31 October 2024, 23:59 CEST.
After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee.

You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/.
Interviews will be held in November 2024.

Københavns Universitet giver sine knap 10.000 medarbejdere muligheder for at udnytte deres talent fuldt ud i et ambitiøst, uformelt miljø. Vi sikrer traditionsrige og moderne rammer om uddannelser og fri forskning på højt internationalt niveau. Vi søger svar og løsninger på fælles problemer og gør ny viden tilgængelig og nyttig for andre.

Info
Ansøgningsfrist: 31-10-2024

Ansættelsesdato: 01-01-2025

Arbejdstid: Fuldtid

Afdeling/Sted: Department of Computer Science

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Københavns Universitet (KU)

Nørregade 10, 1165 København K

Københavns Universitets mål er at drive forskning af højeste kvalitet, at tilbyde forskningsbaseret uddannelse til det højeste akademiske niveau, og at formidle ny og klassisk viden til såvel videnskabelige miljøer som til det omgivende samfund.

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