20 jobannoncer matcher din søgning 20 jobannoncer fundet

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

We seek a motivated, curious, and outgoing PhD candidate with a solid background in optical communication, laser physics or nonlinear optics. Experience with machine learning, digital signal processing and experimental work is a plus.

The project goal is to explore various machine learning techniques to realize feedback control that can enable spectral shaping and quantum noise limited operation. The project will cover both numerical simulations, algorithm development as well as experimental implementations.

PhD scholarship in Silicon Photonics for Optical Neural Networks – DTU Electro

If you want to establish your career as an early-stage researcher and is currently looking for the best possible foundation for your dreams and ambitions, it is right here in front of you. With this PhD position, we offer you the possibility of establishing your career as a scientist in photonic integrated circuits based optical computing.

You will be working in DTU Electro, in the new Photonic Integrated Circuit based Systems (PICSys) group. The setting will be the cutting-edge laboratory for advanced optical and digital signal processing and integrated photonics devices, and the access to one of the largest cleanroom facilities in European Universities.

PhD scholarship in Bioinformatics of the Glycosylation Machinery of Archaea - DTU Bioengineering

DTU Bioengineering seeks a qualified candidate for a fully funded 3-year PhD position within Bioinformatics Based Mapping of N-Glycosylation of Proteins in Archaea. The PhD project is part of a Marie Sklodowska-Curie doctoral training Program, GLYCO-N, funded by the EU (MSCA Doctoral Network).

The PhD project is thus part of a bigger interdisciplinary research effort that aims to 1) Understand the diversity and structural complexity of archaeal, microalgal and viral N-glycosylation and 2) Harness this knowledge for new solutions in biomedicine and biotechnology.

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 digitalization of polymer-based battery electrolyte development - DTU Energy

If you have the ambition to build your scientific career at the forefront of cutting-edge research and contribute to accelerating green transition via digitalization, we have a perfect PhD opportunity for you.

You will work on a project to design fluorinated polymers prepared through light-induced polymerization. The design space for finding the optimal composition and synthesis conditions for polymer electrolytes is too vast to explore manually. Therefore, we are combining self-driving labs, high-throughput atomic scale simulations, and AI to transition to digitalization-based automation of electrolyte development.

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.