120 machine-learning-phd positions in denmark

PhD scholarship in Machine Learning in IoT Edge Devices – DTU Electro

Skip to main content. Profile Sign Out View More Jobs PhD scholarship in Machine Learning in IoT Edge Devices – DTU Electro Kgs. Lyngby, Denmark Job Description We invite applications for a PhD

PhD Studentship in Machine Learning to Predict Nitrogen Leaching at Field Level

available from 1 October 2024 or later. You can submit your application via the link under 'how to apply'. Title PhD position in machine learning to predict nitrogen leaching at field level Research area and

PhD scholarship in Machine Learning Techniques for Spectral Shaping of Ultra-Broadband Optical Frequency Combs - DTU Electro

Skip to main content. Profile Sign Out View More Jobs PhD scholarship in Machine Learning Techniques for Spectral Shaping of Ultra-Broadband Optical Frequency Combs - DTU Electro Kgs. Lyngby

PhD Stipend in Machine Learning for Monitoring Wind Turbine Operation

The project is carried out in a collaboration between Aalborg University and Siemens-Gamesa, and we are seeking a PhD candidate for a project focused on the development and application of machine

PhD Stipend in Federated Analytics and Knowledge Graphs (DKW)

. Additional knowledge and experiences within the following areas are highly appreciated: data analytics, machine learning, federated learning, and data privacy. Outstanding spoken and written communication

One or more integrated(4+4) PhD positions in Advancing Real-Time and Trustworthy Autonomous Systems in Unexplored Environments

operations research, machine learning, and decision-making frameworks, with the ultimate goal of creating real-time autonomous systems that are not only trustworthy, but also adaptive when faced with

PhD position: First-principles Many-Body Methods for Complex 2D Heterostructures at CAMD – DTU Physics

of specific 2D functionalization strategies, we have a broad and flexible focus when it comes to the employed methodologies (empirical models, DFT, many-body perturbation theory, machine-learning) the target

PhD position in Computational Electrocatalysis – DTU Physics

Dynamics (AIMD), and Machine Learning (ML) tools to develop theoretical electrocatalytic frameworks. Hereby, the project will challenge existing research on catalysis, move the boundary of fundamental

Postdoc position in applied machine learning to develop risk prediction tools in atrial fibrillation (2024-224-05934)

multimorbidity patterns in atrial fibrillation patients. The key responsibility of the position is to structure atrial fibrillation patient’s health data for machine learning algorithms(feature engineering

PhD scholarship in Key Determinants of Sustainable Lifestyles - DTU Sustain

Models and Machine Learning techniques able to "let the data speak" and assess interactions between multiple determinants. The present PhD will focus on the sustainability side of the project and the