Sort by
Refine Your Search
-
Category
-
Program
-
Employer
-
Field
-
through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The PhD Program in Economics, Analytics
-
. Specific Requirements ● Master's Degree in Physics, Materials Science or related fields; ● PhD in Physics, Materials Science or related fields. LanguagesENGLISHLevelExcellent Additional Information Website
-
6 Mar 2026 Job Information Organisation/Company CERIC-ERIC Research Field Physics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 30 Aug 2026 - 23:59
-
28 Mar 2026 Job Information Organisation/Company Istituto Italiano di Tecnologia Research Field Engineering Researcher Profile Recognised Researcher (R2) Application Deadline 30 Apr 2026 - 00:00
-
, volcanology, critical raw materials, and machine learning / AI. The network combines advanced petrological observations and multimodal analytical data with modern ML (including physics-informed and generative
-
17 Feb 2026 Job Information Organisation/Company University of Pisa Department Department of Biology Research Field Biological sciences » Biology Researcher Profile First Stage Researcher (R1
-
23 Mar 2026 Job Information Organisation/Company Istituto Italiano di Tecnologia Research Field Engineering Researcher Profile Recognised Researcher (R2) Application Deadline 31 Dec 2026 - 00:00
-
Computer-Assisted Laser Microsurgery,” IEEE Transactions on Medical Robotics and Bionics, https://doi.org/10.1109/TMRB.2024.3468385 , 6(4), pp. 1423-1435, November 2024 ESSENTIAL REQUIREMENTS PhD degree in
-
21 Feb 2026 Job Information Organisation/Company Istituto Italiano di Tecnologia Research Field Chemistry Pharmacological sciences Physics Researcher Profile Recognised Researcher (R2) Application
-
bring Essential PhD Degree in a relevant scientific field (e.g. computer science, data science, mathematics, engineering, or related); Strong understanding of generative models (e.g., VAEs, GANs