-
contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
-
-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
-
research environment focusing on integrating multi-source data and developing novel algorithms to address the challenges posed by global environmental change. You will focus on integrating experiments, field
-
Postdoctoral Researcher Position in Digitalization of Metal Additive Manufacturing and CO2 Impact...
highly motivatedpostdoctoral researcher to contribute to this vision by leveraging digital twins, sensor integration, and data-driven sustainability assessments. The successful candidate will play a key
-
mechanism. Recent developments in protein structure prediction and protein de novo design have opened new possibilities for probing such mechanisms. The project will seek to use existing algorithms to new
-
studies limited to crystalline POMs and remove existing confines imposed on the rational design of tailor-made non-crystalline POMs to meet unmet needs in fields such as energy storage, sensors, catalysis
-
implementing inversion algorithms, including a focus on the integration of spatially constrained regularization schemes. Collaborating with forward modeling experts to ensure seamless integration with a recently