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evaluation methods for vision models Design metrics to compare neural and behavioral data with computational predictions Collaborate with CRC groups on open, reproducible standards for model evaluation Mentor
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regarding the position, please contact Prof. Dr. Renata Motta via hcias-jobs@uni-heidelberg.de . Further information on the HCIAS can be found at www.hcias.uni-heidelberg.de/en . We look forward to receiving
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us We are TUM’s unique Pathology AI lab developing new machine learning (ML) methods for automatically analyzing digital pathology data and related medical data. Such methods include the automatic
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part of the School of Computation, Information and Technology (CIT) of TUM. The position is for 2 years and follows state regulations in accordance with the Collective Agreement for the Public Service
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Postdoc in "Navigating uncertainty: Planning marine protected areas in a changing Southern Ocean"...
states, particularly concerning the balance between conservation priorities and economic interests. In this challenging context, the scientific community must continue to generate robust data and
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-temporal overlaps in the presence of both human and marine mammal activities. By using sighting data and ship positional data, as well as passive acoustic recordings, the project will provide an overview
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. The integration of ink painting into the academic system will be the subject of a fourth case study. Further information on the project: www.chinacademy.fu-berlin.de https://www.geschkult.fu-berlin.de/e/khi
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letter outlining research experiences and interests and two reference letters by July 15th , 2025 to Tobias Raisch at tobias.raisch@mpi-dortmund.mpg.de . Additional Information: The Max Planck Society (Max
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Familiarity with statistical analysis and interpretation of experimental data Experience in scientific writing, especially for publications and third-party funding applications Proficient English and, ideally
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). For further information: Dr. Jethro Hemmann | https://www.leibniz-hki.de/de/mnd-mitarbeiter-innendetails.html?member=1441 |+49 3641 532-1478 | career@leibniz-hki.de Application: Leibniz-HKI is proud to be