35 jobannoncer matcher din søgning 35 jobannoncer fundet

PhD scholarship in Broadband Vibroacoustic Shape Optimization using Model Order Reduction Methods – DTU Electro

This project aims at the application of MOR to the optimization of electroacoustic devices that involve the interaction of mechanical and acoustical domains, i.e. vibroacoustics. At DTU and KUL, you will have access to state-of-the-art knowledge on numerical methods, MOR and numerical optimization.

You will collaborate with the company PURIFI, a research-based producer of high-end loudspeaker units with wide practical experience on transducer non-linearities, measurement methods, and optimization techniques. You will be expected to extend and streamline models, opening up new possibilities for vibroacoustic design.

PhD scholarship in Linearized floating wind farm modelling - DTU Wind

Do you want to be involved in the green energy transition? Do you wish to contribute to the development of advanced technologies for floating wind farms and are you looking for a career in R&D or academia? Then we have a great opportunity!

The overall research goal is to develop a fast linear numerical model facilitating simplified, yet sufficiently accurate, description of a floating wind farm for design of optimal control and optimal layout of such. The model will make out a linearized counterpart to the time domain Dynamiks.HAWC2Farm model.

PhD scholarship in Measurement Methods, Reliability, and Uncertainty in Acoustic-Mechanical Microsystems – DTU Electro

Are you interested in developing and advancing state-of-the-art measurement methods for sound and vibration in miniature audio systems?

The small scale of smart hearables such as ear pods, headsets, and hearing aids present unique challenges to accurately and reliably measure the acoustic and vibroacoustic behaviour of their components. But modelling, simulation, and optimization of such devices relies on accurate measurement data.

As a PhD candidate with us you will investigate and develop measurement methods suitable for small parts and evaluate reliability and uncertainty of these methods.

PhD scholarship in Uncertainty Quantification for Deep Learning - DTU Compute

Do you want to do research on cutting edge machine learning methods?

If you are establishing a career as a researcher in machine learning, and you are motivated to work with the latest methods for quantifying uncertainty in neural networks, we can offer you the best possible foundation.

During the PhD program, you are expected to:

• Develop novel methods for uncertainty quantification in deep learning.
• Work with state-of-the-art nerual network architectures applied to molecular data.
• Publish scientific papers and present research results in top machine learning conferences such as NeurIPS, ICML, UAI, and AISTATS.

PhD scholarship in Efficient Numerical Modelling of Smart Hearables while Fitted to Users – DTU Electro

Are you interested in learning and extending on state-of-the-art numerical modelling techniques and, at the same time, contribute to improving the listening experience of smart hearable users and hearing impaired?

As a PhD candidate with us you will create models of audio devices that are worn in or over the ear and including the wearer’s acoustical and mechanical influence. You will deal with a large modelling task with uncertain input data, and to do this you will acquire knowledge on fields like advanced numerical modelling techniques, improvement of model efficiency and numerical optimization, among others.

PhD Scholarships (2) in Cyber-Security and Cyber-Deception – DTU Compute

The two positions are part of the project Loki: Situational aware collaborative bio-inspired cyber-deception.

This project, inspired by Norse mythology, with Loki being a shape-shifter god and a master of trickery, aims at redefining and evolving the emerging field of cyber-deception. Here, we attempt to deceive attackers by creating fake vulnerable systems that are aware of their surroundings and are constantly shifting.

The project takes inspiration from nature (e.g., from the mimicry phenomenon) to synthesize sophisticated deception.