Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
epidemiology to understand RNA metabolism. Perform stochastic simulations to analyze model behaviors. Fit the model parameters to empirical RNA expression and RNA-protein binding data. Predict outcomes
-
networks are controlled, to develop predictive models of methane cycling in northern rivers. This postdoc position will focus on assessing how stream methane emissions are linked to permafrost thaw, using
-
educational programs, we are now seeking a postdoctoral researcher to work on privacy for data-driven models and high-dimensional data. The position is full-time for two years, starting on 1st September, or as
-
reacting flows. A novel aspect of the project is the use of highly perturbed laminar flame simulations to inform CFD modelling of turbulent combustion in lean hydrogen-air mixtures. Experimental work will be
-
of millions of lakes worldwide. The successful candidate will create innovative solutions that significantly enhance large-scale environmental simulations and meaningfully advance the modeling of global lake
-
design. One of our group's goals is to create efficient surrogate models that reduce the computational cost of MD simulations by several orders of magnitude. Notable examples of our work in this area
-
models into Chalmers’ bridge simulators in collaboration with other researchers. You are also expected to supervise PhD and MSc students and to publish at least two peer-reviewed journal articles during
-
spinal cord as a model system. You will engage a systematic strategy to identify these mechanisms by generating innovative mouse genetic strains, identifying embryonic defects and the underlying molecular
-
environmental simulations and meaningfully advance the modeling of global lake ecosystem dynamics. This is a full-time, two-year position. The application deadline is May 15, 2025, and the expected start date is
-
results into practical applications for end users. Subject Description The research aims to develop machine learning models for microbe detection, focusing on the mathematical foundations in geometry and