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Field
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center fully integrated into the LIGO/Virgo distributed computing network. IFAE is in a privileged position to analyze the LIGO/Virgo/KAGRA data and, in collaboration with IFAE’s teams in CTA/MAGIC and
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the position is filled. REQUIRED EDUCATION AND EXPERIENCE: DEFINITION: The Postdoctoral Appointee holds a PhD or equivalent doctorate (e.g. ScD, MD, DVM). Candidates with non-US degrees may be required
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
, ecosystem state, and krill biomass and distribution. The krill fishery is concentrated in the southwest Atlantic Sector of the Southern Ocean (CCAMLR Area 48), a krill hotspot that supports many krill
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) Positions PhD Positions Application Deadline 20 Mar 2026 - 23:59 (Europe/Warsaw) Country Poland Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 6 Feb 2026 Is the job
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funding is available. Actively participates in the preparation of required technical progress reports for research sponsors. Qualifications Appropriate PhD in a related field. Must be able to perform
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, distributed systems, or large-scale data pipelines Experience with game engines, XR systems, or advanced graphics frameworks applied to scientific data Record of publications in visualization, AI
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. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top
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technique based on CLCE coating. This new technique, combining a novel material coating with a camera-based tracking system, aims to provide a unique spatially-distributed bridge monitoring, leading to new
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with developing distributed programs on high-performance computing systems. Experience in data assimilation and machine learning. A track record of publications in well recognized journals. Special
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distributed devices (smartphones, wearables) to learn from new data streams over time (Continual Learning) while collaborating globally (Federated Learning). Analyze Mobile & Wearable Data: You will work with