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Field
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://martilab.com/ . Trains under the supervision of Prof. Edward Marti including (but not limited to) the following activities: Build and optimize ultrasound rigs and imaging of neonatal and adult rodents (mice and
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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | about 17 hours ago
to Dr. Cyrille Kenne (kenne@math.ubc.ca ) with a cc to Prof. Rashid Sumaila (r.sumaila@oceans.ubc.ca ), along with the subject line “Application for a Postdoc at UBC in Maths for Fisheries”. (B
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RWTH Aachen University, Department of Mathematics Position ID: RWTH -PROF [#26602, BANF 29059] Position Title: Position Location: Aachen, Northrhine-Westphalia 52056, Germany [map ] Appl Deadline
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and physics-based models for battery behaviour. Designing advanced BMS algorithms for real-time monitoring and control. Creating generalizable tools applicable to various battery types, geometries, and
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approaches, sound art, algorithmic governance, media and cultural studies, digital media, environmental approaches, and others. The communities and physical research sites of the project are located in
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collaboration with Prof. Giovanna Tinetti and her team and collaborators at KCL. The main purpose of this role is to develop new and/or to use existing models to simulate the atmospheres of exoplanets and use
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learning algorithms on graphs to model, characterize, predict, and design the thermal and physical behaviors of diverse material systems. Responsibilities also include the development of software codes
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under the supervision of Prof. Edward Marti including (but not limited to) the following activities: Build and optimize ultrasound rigs and imaging of neonatal and adult rodents (mice and rats). Develop
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The Institute for Infection Prevention and Control (IPC, Head Prof. Dr. Philipp Henneke) is looking as soon as possible for a Bioinformatician (m/f/d, PhD) with focus on the analysis of large
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with