PhD Scholarship from DTU University in Denmark with a Funding of €50,000 per Year

The Characterization Section at DTU Nanolab is seeking an outstanding candidate for a position as a Ph.D. student. The main focus of the characterization section is to advance the field of electron microscopy applied to both hard and soft matter. The student will be part of a research project in collaboration with DTU Physics on developing deep learning methods for automated and quantitative analysis of atomic-resolution electron microscopy images acquired both conventionally as well as in situ.

Responsibilities:

1. You will be responsible for electron microscopy characterization at a high resolution of relevant catalyst samples. 
2. Most work will be done in a gaseous environment at elevated temperatures where reaction products can be measured using online mass spectroscopy.
3. Understanding the responses of catalytically active surfaces to changes in the environment and correlating these changes to measured catalytic activity. The data will provide input for automated analysis approaches applying deep learning algorithms developed at Computational Atomic-scale Materials Design (CAMD) at the Department of Physics at DTU.
4. You will be employed in the Characterization Section at DTU Nanolab where you will be working closely with Ph.D. students, post-docs and faculty members using various electron-beam based techniques. 
5. You will be collaborating with the theoretical scientists in the Department of Physics, a leading department in surface science and catalysis.

The Benefits:

1. The position, which involves a limited teaching obligation, includes salary and travel grants covering the three years it takes to obtain a Ph.D. degree at a Danish university. Salary level is approximately 50,000 Euro/year.
2. During your employment as a Ph.D. student, you will acquire expert skills in

• High-resolution transmission electron microscopy.
• In situ experimentation.
• Beam-sample interactions.
•  State-of-the-art machine learning algorithms, in particular, deep learning and convolutional neural networks and modern atomic-scale simulation methods, including Density Functional Theory.

The Conditions:

1. Candidates should have a two-year master's degree in Physics (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. 
2. The candidate should have a good knowledge of solid-state physics.  Experience with electron microscopy is an advantage, but not a requirement. 
3. The candidate has obtained excellent grades in his/her Bachelor and Master educations.
4. The candidate must have good communication skills in both spoken and written English.

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