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Open Positions 1
Time Span 01 May 2019 for 3 years
Application Deadline 28 Feb 2019
Financing yes
Type of Position
  • PhD - Doctoral Programme
Field of Research
  • Engineering
Subjects Software Engineering
Description Factors for effective exploitation of machine learning in light microscopy

Machine learning has developed to a point where several fields of technology where revolutionized, and, in principle, machine learning is now widely applicable as a standard tool. In this situation, the limiting factor is how easily and effectively non-specialists can customize machine learning tools to their everyday work. In your work, you will explore key factors for the effective exploitation of cutting-edge machine learning tools in biological microscopy. Specifically, you will work in the paradigm of “action research”, developing a tool for immediate application and reflecting the work process and experiences of other specialists from the community. The challenge in question is to exceed the physical limitations on the number of color channels that can be recorded by a fluorescence microscope, and thus follow the multitude of molecular processes that contribute to information processing in the cell nucleus. This work will draw on cutting-edge tools such as in silico microscopy (ISM) or Content-Aware image REstoration (CARE), which utilize the image.sc libraries, python as well as TensorFlow as a machine learning core.

We will put you in an ideal position for your work, as you will be embedded in the groups of Profs. Anne Koziolek and Lennart Hilbert at Karlsruhe Institute of Technology. Both groups are very young, and offer direct supervision and frequent access to your supervisors. Anne Koziolek’s background is in software engineering and software architecture. She and her group investigate how to support design decisions and design space exploration in agile software development approaches. She leads the research group “Architecture-driven Requirements Engineering” at the Institute for Program Structure and Data Organization at KIT. Lennart Hilbert’s group combines biological wet lab work, cutting-edge light microscopy, and custom-developed image analysis, to investigate information processing inside cell nuclei. Lennart Hilbert trained at the Center for Systems Biology Dresden, one of the world’s leading centers for light microscopy and image bioinformatics. He now leads the research group “Computational Architectures in the Cell Nucleus” at the Institute of Toxicology and Genetics (KIT) and is Junior Professor for Systems Biology and Bioinformatics at the Zoological Institute (KIT). Besides our own groups, you will be part of the wider HIDSS4Health initiative that spans DKFZ, Uni Heidelberg, and KIT (three of Germany’s very best institutions), and offers a wide array of scientific and soft skill training aspects. You will be able to establish connections with other students of the program, and other specialists and developers via Hackathon and Learnathon events as part of the international ImageJ/FIJI developer community.

To apply, please visit hidss4health.de.

If you have any questions, please contact Anne Koziolek and Lennart Hilbert.

Requirements What we expect from you? The creativity, autonomy, and interpersonal skills needed for this project. We will support you all we can, but you will be driving this project most of the time. Formally speaking, you will need a Master’s degree before starting your PhD with us (not required at time of application). This degree should be in Mathematics, Computer Science, Engineering, Physics, or related fields. Other fields are also perfectly fine, as long as you can demonstrate a strong enough background in programming for this project.
Working Language
  • English
  • German
Language of Dissertation
  • English
Required Documents
  • CV
  • Reports, certificates
  • Transcripts
  • Letter of Motivation
More Information https://are.ipd.kit.edu/theses-and-jobs/hidss4health/

Contact

Karlsruher Institut für Technologie • Institute for Program Structures and Data OrganizationIns
Prof. Dr.-Ing. Anne Koziolek
Am Fasanengarten 5
76131 Karlsruhe

Mail: koziolek@kit.edu
https://are.ipd.kit.edu