Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- NTNU - Norwegian University of Science and Technology
- Technical University of Denmark
- Cranfield University
- NTNU Norwegian University of Science and Technology
- Nature Careers
- Aalborg University
- Tallinn University of Technology
- The University of Manchester
- University of Nottingham
- Wageningen University & Research
- CNRS
- Eindhoven University of Technology (TU/e)
- Empa
- Forschungszentrum Jülich
- Swedish University of Agricultural Sciences
- Utrecht University
- ;
- Chalmers University of Technology
- Delft University of Technology (TU Delft)
- KU LEUVEN
- Linköping University
- Medical University of Innsbruck
- Sveriges Lantbruksuniversitet
- Technical University of Munich
- Umeå University
- University of Adelaide
- University of Birmingham
- University of Exeter
- University of Southern Denmark
- University of Twente (UT)
- University of Warwick
- Vrije Universiteit Brussel (VUB)
- Amsterdam UMC
- CEA
- Centre de Mise en Forme des Matériaux (CEMEF)
- DAAD
- Deutsche Bundesbank
- ENVT INRAE
- Erasmus University Rotterdam
- Helmholtz-Zentrum Dresden-Rossendorf
- Helmholtz-Zentrum Umweltforschung
- Institute of Physical Chemistry, Polish Academy of Sciences
- Instituto Português de Oncologia do Porto Francisco Gentil (IPO Porto)
- Iquadrat Informatica SL
- Itä-Suomen yliopisto
- Josep Carreras Leukaemia Research Institute (IJC)
- KNAW
- Karolinska Institutet, doctoral positions
- Lulea University of Technology
- Luleå tekniska universitet
- Luleå university of technology
- Luxembourg Institute of Science and Technology
- Monash University
- NIOZ Royal Netherlands Institute for Sea Research
- Northeastern University London
- Queensland University of Technology
- Technical University Of Denmark
- Texas A&M AgriLife
- The Belgian Nuclear Research Centre
- The University of Edinburgh
- UNIVERSIDAD POLITECNICA DE MADRID
- University College Cork
- University Medical Centre Groningen (UMCG)
- University of Antwerp
- University of Bergen
- University of Berne, Institute of Cell Biology
- University of Bologna
- University of Cambridge
- University of Cambridge;
- University of Dundee;
- University of Lund
- University of Pisa
- University of Sheffield
- University of Texas at El Paso
- 64 more »
- « less
-
Field
-
of state Developing a semi-primitive approach for the electrostatic forces Predicting solid-liquid equilibria (3) Molecular thermodynamics for inhomogeneous electrolyte systems Developing classical density
-
class of hydrogels that offer superior control and consistency, aligned to pharmaceutical standards. The potential benefit is to enhance the consistency and predictability of tissue cultures, with
-
predictive models for evaluation of the role of dietary in health and disease and establish personalized dietary strategies for more effective disease prevention. In many cases, the work involves time series
-
of diagnostic and prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining useful life of electronic components, supporting studies in electronic
-
prognostic algorithms. Electronic Prognostics Systems: Facilities equipped to assess the health and predict the remaining useful life of electronic components, supporting studies in electronic system
-
translational medicine using a "bench-to-bedside" approach. By harmonising and analysing diverse biomedical data, while focusing on the secure data processing and predictive modelling, we aim to drive progress in
-
sensors - if we can control and tune their properties. You will develop and use top-of-the-line machine learning models to predict the sensor response of these materials under realistic conditions
-
Infrastructure? No Offer Description The PhD candidate will work on the development of advanced statistical and machine learning methods for time series prediction, with applications mainly in the field of traffic
-
. The objective of this PhD project is to develop AI methodologies for the analysis part of condition monitoring (CM) and predictive maintenance (PM). The primary challenge in predictive maintenance lies in