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appointment, with renewal up to three years possible based on performance Appointment Start Date: September 1, 2026 Group or Departmental Website: https://mpolyak.people.stanford.edu/ (link is external) How
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log into Workday, type "Find Jobs" in the search box which will navigate to the internal job posting site. Locate this specific job posting by typing the job requisition number, "R0150117" in the search
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Skip to Main Content Toggle navigation Home Search Jobs Job Alerts Log In /Create Account Help Post Doc Res Assoc Bookmark this Posting Print Preview | Apply for this Job Announcement Details Open
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partners to develop new training and support initiatives Providing mentorship and guidance to PhD students and early career scholars navigating diverse career pathways Contributing to HRC programming, events
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clock. Our research program uses various nonâ‘model species and a hypothesis driven, systems approach to examine how these factors impact plant defense. We explore how plants have navigated the fine line
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sensing in naturalistic environments of flying Drosophila . Research Projects Olfactory Navigation: Investigating neural circuits and behavioral strategies underlying odor-guided navigation in complex
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 1 month ago
). For the second goal, we propose to build on the previously collected examples to characterize stages of tailoring tasks such as answering automatic suggestions from the system, navigating menus to find
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uses various non‑model species and a hypothesis driven, systems approach to examine how these factors impact plant defense. We explore how plants have navigated the fine line between growth and defense
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Skip to Main Content Toggle navigation Home Search Jobs Job Alerts Log In /Create Account Help Post Doc Res Assoc Bookmark this Posting Print Preview | Apply for this Job Announcement Details Open
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, particularly in the domain of Positioning, Navigation, and Timing (PNT). The research aims to generate and evaluate the quality of synthetic PNT data created using pre-trained foundation models (FMs) such as