Postdocs or researchers to work in the interdisciplinary research project Hierarchical Analysis of Temporal and Spatial Data (HASTE)

We are recruiting up to three postdocs or researchers to work in the interdisciplinary research project Hierarchical Analysis of Temporal and Spatial Data (HASTE),
see, within the research groups of Prof. Carolina Wählby,
see, Assoc. Prof. Andreas Hellander,
see and Assoc. Prof. Ola Spjuth,

Research project: You will join a recently started project that will run for 5 years and which is funded by the Swedish Foundation for Strategic Research (SSF). This interdisciplinary project aims at developing new, intelligent ways of processing and managing very large amounts of microscopy images in order to be able to leverage the imminent explosion of image data from modern experimental setups in the biosciences. One central idea is to represent datasets as intelligently formed and maintained information hierarchies, and to prioritize data acquisition and analysis to certain regions/sections of data based on automatically obtained metrics for usefulness and interestingness. To arrive at such smart systems for scientific discovery in image data, we will pursue a range of topics such as efficient data mining in image data, machine learning models with quantifiable confidence that learn an objects interestingness, and development of intelligent and efficient cloud systems capable of mapping data and compute to a variety of cloud computing and data storage e-infrastructure based on the quality and interestingness of the data. Project partners are at the Department of Information Technology, Uppsala University, Department of Pharmaceutical Biosciences, Uppsala University, Vironova AB and AstraZeneca AB.

We are currently seeking to fill three roles in the project. More information about the specific projects can be found on the project webpage:

  • Detection of informative data from large-scale spatial and temporal experiments (with placement in the Wählby lab)
  • Smart systems for creation and maintenance of information hierarchies in multi-cloud environments (with placement in the Hellander Lab)
  • Machine-learning with quantifiable confidence or probability (with placement in the Spjuth lab)

We welcome applications no later that 2017-05-23. All applications must be submitted via the online recruitment portal. See for more information.