Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
(by depositing metal in the space between the NDs) or networks of 2D metal pads formed on the domains. Our team has good experience in the formation of hybrid nano-objects (organo-metallic
-
metal in the space between the NDs) or networks of 2D metal pads formed on the domains. Our team has good experience in the formation of hybrid nano-objects (organo-metallic) on the surface of water by
-
cell tracking to identify the progenitors of these cells during regeneration. • Develop and apply a recombinase-based cell barcoding strategy to trace cell lineages during leg growth and regeneration
-
. The inventory is still ongoing, but our field is now heavily investing in the characterization of the physical and chemical properties of these objects through the use of sensitive imaging cameras and
-
Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The objective of this postdoctoral position, in
-
, such as Bayesian approaches and fossilized birth–death models, to reconstruct robust phylogenies and estimate divergence times. It also investigates macroevolutionary dynamics, including variation in
-
Description You will: * Lead MEG head-cast data collection for a visuomotor reaching/interception study, ensuring robust synchronization with video-based kinematics and eye-tracking, and enforce rigorous
-
: proficiency in Monte Carlo simulation codes, such as GEANT 4 or PENELOPE. Bayesian statistics. • Laser polarisation system: appetite for experimental physics, experience with lasers not required but would be a
-
implementing models that integrate ecological dynamics, species traits, phylogenetic trees, and economic discounting; ● Devising Bayesian or POMDP frameworks to handle uncertainty about species interactions
-
applications. The project aims to address fundamental theoretical questions related to the representation and measurement of the polarization state, as well as the use of Bayesian and/or statistical learning