Scientist / Postdoc (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM)

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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early diagnosis, and

therapy of diseases like cardiovascular diseases, autoimmune diseases or cancer. Overall, the institute strives to advance precision medicine by combining knowledge from different fields such as biology,

chemistry, pharmacology, physics, and computer science. ISAS is a member of the Leibniz Association and is publicly funded by the Federal Republic of Germany and its federal states.


At our location in Dortmund we invite applications for a


Scientist / Postdoc (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM)


You will be responsible for:


  • Develop scalable microscopy image analysis workflows for real interdisciplinary applications in biomedical research
  • Develop multi-modal machine learning algorithms for integrating multiomics analytical data and microscopy image data
  • Establish FAIR microscopy data management system within the institute
  • Work with software engineers and students in the team to build public AI-ready data portal
  • Coordinate interdisciplinary cross-team projects and lead the development of computational tools
  • Report findings and methods in conference and journal papers
  • Conduct software demo and tutorials at national and international workshops


Your profile:


  • University degree in computer science/computer engineering/statistics/applied mathematics/data science/biomedical engineering or of relevant scientific field
  • A solid background in machine learning
  • Extensive experience in either general computer vision or microscopy image analysis
  • Extensive hands-on skills with Python and PyTorch
  • Experience with foundation models (vision large models or multi-modal large language models)
  • Good presentation and writing skills
  • Proactive, independent, and solution-oriented way of working
  • Fluent English (spoken and written)
  • Publications at top-tier computer vision conference or journals is a plus
  • Experience with open-source software development is a plus


We offer:


  • Scientific development opportunities in an international cooperative, interdisciplinary research environment and an excellent working atmosphere in a very dynamic and professional team
  • Extensive state-of-the-art equipment and infrastructure, including sufficient GPUs for machine learning model development
  • The opportunity to present your data on international conferences and participate in workshops


Non-residents who apply for this job will receive help from the institute to find accommodation and to handle authorities. Applications from disabled applicants are welcome. ISAS supports the principle of equal opportunity for all employees and therefore particularly encourages women to apply.


The salary will be according to the German TV-L. The full-time position is available immediately and offered for three years. The position is generally suitable for part-time.


ISAS collects and processes the personal data of its applicants in accordance with European and German legal regulations. Further information on data protection and the processing of personal data can be found at www.isas.de/datenschutzhinweise-fuer-bewerberinnen-und-bewerber.


The closing date for applications is September 21, 2024. Please apply via our applicant portal. Informal requests (reference number 313_2024) are welcome and can be directed to the Human Resources team (bewerbungen@isas.de). Further information about the institute can be found at:

http://www.isas.de/en.


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10899



Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. (ISAS)



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Deadline: 2024-09-21
Location: Germany, Dortmund, Nordrhein Westfalen
Categories: Applied Mathematics,, Biomedical Sciences, Computer Engineering, Computer Sciences, Data Science, Machine Learning, Postdoc, Scientist, Statistics,

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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. (ISAS)


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