64 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" scholarships at Nature Careers
Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Field
-
websites. Application Process Applications for both programs must be submitted online by January 14, 2026: https://www.uni-goettingen.de/de/application/556704.html Applicants will be asked to upload a CV
-
applicants in accordance with European and German legal regulations. Further information on data protection and the processing of personal data can be found at: https://www.isas.de/en/datenschutz . The closing
-
. Benefits and salary The successful candidates will receive an attractive salary in accordance with the MSCA regulations for Early-Stage Researchers (http://ec.europa.eu/research/mariecurieactions
-
mentorship. Application deadline: 27h of February 2026 at 23:59 hours local Danish time Please see the full call, including how to apply, on https://fa-eosd-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI
-
Declaration of interest regarding PhD project within the field of biomarker and therapeutic targe...
, or pediatric diseases (prior experience is an advantage but not required) Experience with or willingness to learn biomarker analyses (e.g. ELISA), histological techniques, and molecular assays Interest in animal
-
of novel mechanistic insights is gained through the application of novel probabilistic deep-learning models that automatically extract biological and statistical knowledge from your in vivo perturbational
-
catalysts for the synthesis of a range of industrially valuable compounds. This PhD project is part of the Horizon Europe Marie Sklodowska-Curie Action (MSCA) doctoral network (DN) ELEGANCE (machinE LEarning
-
(https://www.cliccs.uni-hamburg.de/about-cliccs/cliccs-ll.html ). In CLICCS-M4, we are further developing the unique ICON-Coast model within the ICON Earth System Modelling Framework. The objective
-
local Danish time Please see the full call, including how to apply, on https://fa-eosd-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/da/sites/CX_1001/job/3497/?utm_medium=jobshare
-
of novel probabilistic deep-learning models that automatically extract mechanistic and statistical knowledge from your in vivo perturbational omics data. This interdisciplinary atmosphere has been a main