Sort by
Refine Your Search
-
neuron electrophysiology as well as complex network dynamics in the context of specific perturbations. You will use these data to map the disease in terms of electrophysiological dynamics and stratify
-
reaction engineering. Proficiency in Aspen Plus or similar process simulation tools. Experience with techno-economic assessments (TEA) of complex chemical or biological systems. Familiarity with CO2 capture
-
which RNAs to continue translating and which to degrade? Our current understanding suggests this results from a complex and not yet fully understood interaction between chemical tags attached to the RNA
-
machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and
-
Institute for Meteorology. YOUR PROFILE We are looking for a curiosity-driven and conceptually-minded candidate who enjoys scientific discussion and complex data analysis. To be considered for this position
-
of the components of the climate system. As a suitable candidate you, have expertise in analyzing complex systems (e.g., using dynamical systems theory, statistical physics) and/or process-level expertise in a
-
Institute for Meteorology. YOUR PROFILE We are looking for a curiosity-driven and conceptually-minded candidate who enjoys scientific discussion and complex data analysis. To be considered for this position
-
, production-grade machine learning solutions for predictive modelling and complex decision-support systems. Develop scalable and efficient ML pipelines using MLOps best practices. Address challenges related
-
characterization (e.g. NMR), biofilm extracellular polymeric substances, biophysics, glycoconjugates, complex assembly, or lectins, is an advantage. Your profile Applicants should hold a PhD in glycobiology
-
variable and climate-sensitive ecosystems, which poses great challenges for their mapping. You will be part of a research project aiming to unravel the complex interactions within peatland ecosystems using