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PhD scholarships on “Live” Visualizations of Single Nanoparticle Catalysts at the Atomic-Scale - DTU Physics

Could you envision “seeing” chemical reactions being catalyzed at the atomic-scale? Two or more scholarships are now open for experimental research in nanoparticle catalysis using advanced operando electron microscopy at the Center for Visualizing Catalytic Processes (VISION).

VISION is developing and applying a new unique platform for visualizing catalytic nanoparticles and reactions at the atomic-level by integrating cutting-edge electron microscopy, microfabricated nanoreactors, nanoparticle synthesis and computational modelling. This approach enables new, direct operando observations that are urgently needed to advance mechanistic insight into catalytic processes at the atomic-scale.

Experienced Electronics Engineer in R&D

Are you enthusiastic about product development and envision collaborating with a team who shares your passion?

For our Headquarter in Hillerød, we are seeking a lead electronics engineer who thrives on collaborative teamwork to join our ambitious group of developers in FOSS R&D. In this role, you'll contribute to building the groundwork for cutting-edge instruments, from initial technology concepts to final solutions.

Senior DeltaV Engineer

Cognizant is looking for a Senior DeltaV Engineer to commission and qualify DeltaV projects with our Danish customer on-site/hybrid in Hillerød. This full-time Senior DeltaV Engineer hybrid role comes with a generous salary and benefits package.

As part of the C&Q Team, the Senior DeltaV Engineer will be on-site and eventually perform remote support, including on-call and weekend support. You will be part of state-of-the-art development, working with the strongest, most growing industry in the Nordics.

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.