Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
Two postdoctoral positions (3-year) in Experimental Evolution of Methanogenic Microbiomes in Bioe...
performance and stability. You will work closely with modelling and reactor-focused colleagues to integrate evolutionary outcomes across scales. Your tasks will be: designing and running experimental evolution
-
eager to bring fluorescence microscopy and machine learning together to advance microplastic detection, we strongly encourage you to apply. Job description Design and implement chemometric and machine
-
work closely with other team members to design and implement strategies for the targeted delivery of various oligonucleotide cargoes (e.g., ASOs, siRNAs). A central aspect of the role involves evaluating
-
and Trust (SnT) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role in
-
and Trust (SnT) at the University of Luxembourg is a leading international research and innovation centre in secure, reliable and trustworthy ICT systems and services. We play an instrumental role in
-
leading scientists, all working at the technological edge of modern electron microscopy for advancing catalysis science. The four topics are: 1. Designing Superior Catalytic Sites You will explore
-
patient-derived xenografts and genetically engineered mouse models to inform better immunotherapies for treating high-risk neuroblastoma. Key Responsibilities Design and conduct experiments investigating
-
Ingelheim’s innovation ecosystem with highly motivated, young fellows, who will help to build on science to develop new medicines; and train the next generation of leading scientists. Our campus community
-
this understanding to design therapeutic strategies to overcome them. Our immediate objective is to fully understand the genetic and molecular basis of antifungal resistance in clinical isolates of C. auris
-
your scientific and professional skills by: Designing and leading analyses that apply state-of-the-art generative machine learning models (e.g., VAEs, GANs, transformer-based models) to large-scale