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Fondation Sciences Mathématiques de Paris Position ID: 718-IP [#27729] Position Title: Position Type: Fellowship or award Position Location: Paris, Ile-de-France 75005, France [map ] Subject Areas
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wildfire effects and forest resilience in Douglas-fir/western hemlock forests of the western Cascades. Work will be conducted in field setting on the H.J. Andrews Experimental Forest (https
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. The resulting instrument will have many applications; notably, it will allow the spectroscopic characterization of nanoscale volumes in frozen cell sections, providing unprecedented maps of the distributions
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Social and Historical Sciences. For more information, please visit http://www.ucl.ac.uk/about UCL Mechanical Engineering UCL Mechanical Engineering has been pioneering the development of engineering
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datasets (species and regions to be defined) • implement a generic land use map in the region concerned • design a protocol to compare the results with the actual trajectories • explore the simulation
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maps linking component geometry, process parameters, and performance requirements. Investigating joining and repair methodologies for assembling and maintaining reactor components such as cooling
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of hire Good verbal communication skills are required Ability to perform basic mathematics Computer skills including familiarity with word, excel, and adobe is preferred, to include basic blueprint and map
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 8 days ago
to knowledge production and dissemination. The wider RegNet community reflects these values and is comprised of diverse networks nurtured through deep and sustained engagement. Read more about RegNet: http
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CNRS, LAPTh Position ID: CNRS-LAPTh-PD [#31091] Position Title: Position Type: Postdoctoral Position Location: Annecy, Rhone-Alpes 74940, France [map ] Subject Area: Cosmology/Particle Astrophysics
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developing physics-aware models that bidirectionally map between non-quantitative and quantitative MRI data. Using Bloch equation simulations and cycle-consistent learning, you will create physics-invariant