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Send your CV along with a motivation letter to chloe.lehoucq@pasteur.fr with benjamin.devauchelle@pasteur.fr in Cc. The candidate should have a PhD in Neuroscience or Cognitive science and the
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external research groups, and a planned experimental program in biophotonics. The position is based at Schloss Kränzlin near Neuruppin in Brandenburg — a quiet, focused environment for deep scientific work
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Researcher (R1) Positions PhD Positions Application Deadline 31 Jul 2026 - 14:01 (Africa/Abidjan) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 36 Offer Starting Date 2 Nov 2026
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application! We are looking for a PhD student in biomedical engineering with a focus on deep learning for medical images Your work assignments The position focuses on developing methods for federated learning
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strategy and management. These journals are listed on ERIM´s webpage: https://www.eur.nl/en/erim/erim/journal-list . Your work will also be published as a PhD dissertation. Cooperation To strengthen your
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. This position offers an exciting opportunity to work in a dynamic, innovative research environment. Labor Contract: https://ucnet.universityofcalifornia.edu/labor/bargaining-units/px/index.html Lab: https
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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University Tandon School of Engineering The Dynamical Systems Laboratory at NYU Tandon School of Engineering is seeking to hire a Post Doctoral Associate to work on the mechanics of deep-sea sponges. We seek
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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. The researcher will develop novel research that applies advanced data science, machine learning and deep learning to various different data modalities. An ambition of this team is to implement predictive modelling