Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
Geophysics – OGS announces a public competition, based on qualifications and examinations, for the recruitment with a full-time permanent contract of one (1) staff member in the profile of Researcher – Level
-
Postdocs in Generative Machine Learning for Biomedical Data. The postholders will focus on developing and applying state-of-the-art generative models (such as VAEs, GANs, and transformer-based architectures
-
accelerators Hardware–software co-design for AI and transformer-based models. Responsibilities Conduct cutting-edge research in parallel computing and AI accelerators Develop and lead externally funded projects
-
, spectral matching against databases (e.g., Metlin, KNAPSAcK), and statistical modeling for biomarker discovery. Integration and Interpretation: Correlate metabolomics data with biological and geographical
-
on advanced (nano)materials—particularly single‑atom materials (SAMs) on carbon platforms—and their interactions with relevant cellular models in nanomedicine and nanotoxicology. You will join an international
-
including D-branes, Black Holes, Gauge/string theory duality, Phenomenological String theory/M-theory; Particle Phenomenology including Physics beyond the Standard Model, Dark Matter, Axions, Higgs and
-
Mediterranean culture in the heart of one of Europe’s most exciting mountain regions. Tasks: Development of software to simplify and streamline access to public, remote and cloud-based MS data, including
-
. Massimo De Vittorio and Prof. Gianni Ciofani. You will share with the team the main responsibility of developing of investigating fiber-optic-based methodology to optically irradiate novel chemical
-
-world applications and industrial production lines. Quondensate project aims to achieve the first proof-of-concept of Quantum Reservoir Computing (QRC) scheme based on networks of Quantum Materials (QMs
-
Genomics and single-cell Genomics Sequencing platforms. The successful candidate will take on the following responsibilities: conduct CRISPR-based functional screening using patient-derived cancer tumoroids