Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
experimental data are now available or it may use population-scale genetic, clinical, or public health data from pathogen surveillance efforts and biobanks. The future of life science is data driven. Will you be
-
optimisation algorithms for quantum routing using genetic algorithms (GA), ant colony optimisation (ACO), and particle swarm optimisation (PSO), optimising cost functions subject to entanglement fidelity
-
on high-fidelity modelling and test data for both metals and thermo-set composite materials. To achieve this we will explore the use of advanced genetic algorithms and/or Artificial Intelligence (AI
-
complexity of genetic evaluations are expanding rapidly. For example, for methane emission different recording techniques might be used, records might be collected at different biological stages or in
-
Evolutionary Bias Database for Nucleic Acid Structures (NA3D4U) Built with Help of AI Development and integration of microbial biomass database with AI supported collection and validation of data Genetic-Code
-
complex biological systems. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable
-
from vascular lesions and blood, combined with genetic, clinical/epidemiological and imaging parameters from patients. We also perform in depth functional studies in animal and cell culture models
-
. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable implementations. By
-
of genetically encoded agents, primarily for photoacoustic and fluorescence imaging.Using technologies like photoacoustic imaging, we seek to visualize small populations of labeled cells (e.g. immune cells) deep
-
); execute PoCs and tech transfer with foundries, equipment/materials/metrology vendors. Data & Platforms: Establish robust data governance and MLOps pipelines; develop reusable algorithms and prototype