30 distributed-algorithm-"Fraunhofer-Gesellschaft" Postdoctoral positions at Nature Careers
Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
advanced AI algorithms to optimize and understand the optical properties of light-trapping surfaces. (more information can be found in the following News post ). You will work closely with colleagues both
-
actively contribute to the WeForming and EnerTEF projects. WeForming and EnerTEF propose developing automatized and intelligent solution for operating active distributed grids with multiple active asset6s
-
attacks Develop and implement ML algorithms to identify vulnerabilities and predict potential threats in supply chain systems Prepare project deliverables and disseminate results through high-quality
-
programming of algorithms. The use of programming languages such as Python, R, SQL, and C++ will be a daily part of the project, and proficiency in these languages is required. However, additional datasets will
-
. the genetic `capabilities’) is distributed and maintained across community members, and how these distributions of functions shape ecosystem-level properties. Answering these questions in a host-associated
-
skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
-
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
-
academic and professional qualifications Proven research experience in the field of modelling and analysis of biological networks Solid foundation in mathematics and algorithmic design Strong programming
-
surface properties. Many of these properties are believed to represent adaptations to specific environmental conditions, resulting in distinct distributions of certain combinations of leaf properties
-
neural networks under symmetry constraints, their optimization dynamics, and their generalization behavior—particularly in low-data or out-of-distribution settings. The work combines formal theoretical