Postdoc­toral Re­searcher in Deep learn­ing for Bioim­age Pro­fil­ing

Updated: about 1 month ago
Job Type: FullTime
Deadline: 03 Oct 2021

The Institute for Molecular Medicine Finland (FIMM) is an international research institute focusing on human genomics and personalised medicine at the University of Helsinki. In the beginning of 2017 FIMM joined the University of Helsinki’s new life science research centre, Helsinki Institute of Life Science HiLIFE, as an operational unit. FIMM integrates molecular medicine research, technology centre and biobanking infrastructures under one roof, promoting translational research in grand challenge projects, specifically, the impact of genome information from the Finnish population in personalised health and medicine, individualised cancer medicine, and digital molecular medicine. FIMM is part of the Nordic EMBL Partnership for Molecular Medicine, composed of the European Molecular Biology Laboratory (EMBL) and the centres for molecular medicine in Norway, Sweden and Denmark, and the EU-LIFE Community.

FIMM is currently seeking

Postdoctoral Researcher in Deep learning for bioimage profiling (Paavolainen’s group)

Description:

Your research will focus on novel deep learning methods and models for profiling fluorescence microscopy image data of cancer cell and tissue samples. The developed technology will be used in cancer research to enable 1) more accurate and automated profiling of cells / tissues, and 2) to enable finding novel patterns from the data relevant for the studied biological question. Our aim is to learn general models that are usable for various datasets and research questions.

You will be a member of recently established Lassi Paavolainen’s research group (https://www2.helsinki.fi/en/hilife-fimm/bioimage-profiling-paavolainen ). The research group started its operation in Autumn 2021. We are working actively in collaboration with FIMM and HiLIFE research communities and our international partners. We are using image data prepared together with our collaborators and available in public databases.

In this position you are expected to

  • Do research on novel machine learning methods and models, and implement these
  • Present your work to colleagues and to the international community
  • Publish your research, code and data
  • Participate in writing funding applications
  • Participate in creating a supportive, stimulating and friendly research environment.

Qualification and experience:

The successful candidate should

  • Hold a PhD degree (or similar, or graduating soon) in computer science, machine learning, computational biology or related field
  • Have thorough machine learning, especially deep learning, experience
  • Have image analysis experience
  • Have at least Python programming skills and previous experience in at least one deep learning framework (TensorFlow or PyTorch etc.)
  • Be fluent in English, have good interpersonal and communication skills and be able to work independently as well as within a team
  • Have good problem-solving and analytical skills
  • Earlier experience in fluorescence microscopy imaging data of cells and/or tissue is not essential but beneficial

Salary and contract:

The salary will be commensurate with qualifications based on the university salary system. A contract will be offered initially for two years. Extension beyond this is possible depending on the availability of funding. A six-month trial period will be applied.

To apply for the position, please send your application including motivation letter and CV, including list of publications and contact information for two references, as a single pdf file through the University of Helsinki electronic recruitment system by clicking on the Apply link. Internal applicants (i.e., current employees of the University of Helsinki) please submit your applications through the SAP HR portal. Please apply no later than Oct 3rd 2021. The employment may begin as soon as possible or latest Jan 1st 2022.

For further information please visit our website at http://www.fimm.fi or contact the PI Lassi Paavolainen (lassi.paavolainen@helsinki.fi ).

Due date

03.10.2021 23:59 EEST


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