39 computational-physics-phd-"https:"-"ESPCI-Paris---PSL" Postdoctoral positions at Nature Careers
Sort by
Refine Your Search
-
). We seek an outstanding, ambitious, and highly motivated candidate with a PhD degree in chemistry (or equivalent), preferably with expertise in physical chemistry, theoretical chemistry or computational
-
Postdoc in experimental studies of phase behavior of ABC-miktoarm star block copolymers in thin f...
Experience with image analysis Experience with coding and high-performance computing, for example in python, C, etc. Experience with polymer and/or block copolymer physics and/or chemistry Experience with
-
and field monitoring work performed by a PhD student at LIST and other researchers in LAFI, and extend the existing Vegetation Optimality Model (VOM, https://vom.readthedocs.io ) to test the following
-
, Applied Physics, Plasma processing for materials. Experience and skills PhD in Materials Science, Applied Physics, Plasma processing for materials. 3 to 5 years proven experience in an international R&D
-
influence the adaptability and evolvability of diploids and polyploids. Your profile You have a PhD in Computational Biology, Evolutionary Biology, (Bio)Engineering, Mathematics or Physics. You have expertise
-
data from the European XFEL facility at DESY. Project website: https://www.mpinat.mpg.de/628848/SM-Ultrafast-XRay-Diffraction Your profile Eligible candidates have strong skills in computational physics
-
preparing results for publication. Qualifications MINIMUM QUALIFICATIONS: PhD (or equivalent) in biology, data science, computer science, bioengineering, physics, or a related field. A strong publication
-
from over 50 nations, it is the largest institute of the Max Planck Society. The Department of Theoretical and Computational Biophysics (Prof. Dr. Helmut Grubmüller) is inviting applications for a PhD
-
/articles/s42256-024-00821-x, https://pubs.acs.org/doi/10.1021/acs.analchem.5c06256, https://www.nature.com/articles/s41570-023-00570-2). The research is computational in nature but involves close
-
. The candidate will lead computational analyses of these datasets, using the laboratory’s suite of existing AI/ML tools to assign structures to unidentified peaks in metabolomic datasets (e.g., https