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Field
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Modeling: Generating and maintaining patient-stratified iPSC lines and innovative 3D "brain chimeroid" models. o Advanced Neurophysiology: Assessing functional network activity and synaptic dynamics using
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: Expert knowledge on coupled 3D hydrodynamic-biogeochemical models and agent-based models Expert knowledge of marine physical- and biogeochemical processes in coastal and/or open waters Very good skills in
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representations, and flow matching) for uncertainty-aware 3D reconstruction of coronary anatomy from 2D X-ray angiography; develop physics-informed neural networks and graph-based neural operators for fast
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further insight into the distribution of chemical elements and 3D strain around the interfaces in these structures. The expected results include a better understanding of the growth mechanisms of Sn on III
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Explore opportunities for collaboration with researchers in SPH and across the University to expand and lead research initiatives to support the Collaborative Mentor postdocs and students within
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engineering mindset as additional components will need to be designed and constructed, e.g., using 3D printing, and incorporated into the LCE shells. This is an interdisciplinary Ph.D. research project with
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will work with researchers in environmental geo-spatial AI method development, soil modelling and spatial statistics. Where to apply Website https://www.academictransfer.com/en/jobs/362722/phd-position
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an open research position for a talented and motivated researcher. Motivation Conventional cameras capture two-dimensional images, even though our world is three-dimensional (3D). This lack of depth
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complementary information on 3D structure (GEDI lidar, BIOMASS P-band radar, NISAR L-band radar) and high spatiotemporal resolution (Sentinel‑1 C-band radar, Sentinel‑2 multispectral). State-of-the-art foundation
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(EO) data can be used to assess different facets of ecosystem functioning in grasslands and forests. Within the project, you will collaborate closely with other PhDs and postdocs to collect field data