Sort by
Refine Your Search
-
hybrid quantum-classical or quantum-AI approaches. Projecting short- to medium-term advances in hardware and algorithmic development for practical deployment. Salary Range: €47,273 - €53,925 per annum
-
for complex geological properties. Collection of geochemical and petrological reference data to train models is an equally important component of this task. The post will involve spectral, petrophysical, and
-
of the applicant will be either computational biology, wet-lab or a hybrid of both depending on the successful candidates expertise. There will be strong opportunities for continued professional development as part
-
on ensuring transparency through citation of source material and developing methods to quantify statistical uncertainty in generated outputs. The post-holder will collaborate with a multidisciplinary team
-
the UCD School of Mathematics and Statistics. The successful candidate will lead research focused on developing a scalable, AI-driven quality control (QC) system for synoptic and climate observation data
-
Biosystems and Food Engineering. This project is funded by BiOrbic, Ireland's National Bioeconomy Research Centre. BiOrbic is a national collaboration of researchers, focused on the development of a
-
shortages and complex referral pathways. This role will develop a reliable, scalable, and agent based simulation model that will support caseworkers in developing their care plans for survivors. By analysing
-
within School of Biosystems and Food Engineering. Applications are invited for a Postdoctoral Scientist role within the BiCO project at UCD Algae Group. BiCO is developing a breakthrough technology that
-
within School of Biosystems and Food Engineering. Applications are invited for a Postdoctoral Scientist role within the BiCO project at UCD Algae Group. BiCO is developing a breakthrough technology that
-
statistical analysis of proteomic, phosphoproteomic and related multi omics datasets. The role will contribute to the School's research activity by developing robust, reproducible analytical workflows