Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
Academically relevant background within marine control/cybernetics, computer science, or hydrodynamics, with good skills in mathematics, programming, and machine learning. Master's degree in control engineering
-
Academically relevant background within marine control/cybernetics, computer science, or hydrodynamics, with good skills in mathematics, programming, and machine learning. Master's degree in control engineering
-
Learning Apply for this job See advertisement This is NTNU NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three
-
of Information Security and Communication Technology has a vacancy for 1 PhD Research Fellow in Privacy Preserving Machine Learning. The successful candidate will be offered a 3-year position. Are you motivated
-
Master's degree in Computer Science, Artificial Intelligence, Data Sciecnce (with a focus on machine learning) or equivalent. Your course of study must correspond to a five-year Norwegian course, where 120
-
in crystalline rocks. Drilling optimization using machine learning, e.g. predicting rate of penetration (ROP) and wear. Investigate the possibilities in automation and robotization and the use
-
to your work duties after employment. Required selection criteria You must have a relevant Master's degree in Computer Science, Artificial Intelligence, Data Sciecnce (with a focus on machine learning
-
machine learning, e.g. predicting rate of penetration (ROP) and wear. Investigate the possibilities in automation and robotization and the use of artificial intelligence. Electric drilling and other methods
-
Cybernetics at NTNU is offering a fully funded PhD position in the area of learning-based control and decision-making for complex multi-agent systems. The project explores new computational frameworks
-
renewable energy generation.KU Leuven leads Modelling and Optimization, which focuses on: Developing hybrid models combining first-principle and machine learning approaches. Creating predictive frameworks