PhD scholarship in Machine Learning for Assisting Atomic-Resolution Electron Microscopy

fredag 19 jul 19

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Frist 15. september 2019
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The section for Computational Atomic-scale Materials Design (CAMD) at the Department of Physics is seeking an outstanding candidate for a position as PhD student.  The main focus of CAMD is developing and applying modern simulation methods and machine learning methods within the field of solid-state physics and atomic-scale materials physics.

The student will be part of a research project in collaboration with DTU Nanolab on developing deep learning methods for automated and quantitative analysis of atomic-resolution electron microscopy images.

Responsibilities and tasks
You will be responsible for developing methods that enable electron microscopists to analyse their data on the fly and identify interesting “events” in image sequences, and methods that can extract information from images series that is not normally available in transmission electron microscopy, such as information about chemical elements and 3D structures.  With machine learning, we expect to be pushing the boundaries for what is possible to achieve with electron microscopy.

You will be employed in the CAMD group consisting of four faculty members and 20 PhD students and postdocs.  You will be collaborating with the experimental scientists in DTU Nanolab, a leading laboratory for electron microscopy.

During your employment as a PhD student, you will acquire expert skills in
 

  • State-of-the-art machine learning algorithms, in particular deep learning and convolutional neural networks.
  • Modern atomic-scale simulation methods, including Density Functional Theory.
  • Development of scientific software.
  • Transmission electron microscopy.
If this sounds interesting, you may be our new PhD student!

Qualifications
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. 

The candidate should have a good knowledge of solid-state physics.  Experience with machine learning and/or computational physics is an advantage, but not a requirement, as is programming experience (Python, C, C++ or similar).  The candidate has obtained excellent grades in his/her Bachelor and Master educations and has good communication skills in both spoken and written English. 

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see the DTU PhD Guide.   

Assessment
The assessment of the applications will be made by Professor Jakob Schiøtz, DTU Physics. 

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.  The position is available immediately and should start in 2019.

The position, which involves a limited teaching obligation, includes salary and travel grants covering the three years it takes to obtain a PhD degree at a Danish university. Salary level is approximately 50.000 Euro/year incl. pension. 

You can read more about
career paths at DTU here.

Further information
Further information may be obtained from Professor Jakob Schiøtz, email: schiotz@fysik.dtu.dk.   

You can read more about department of Physics and the section for Computational Atomic-scale Materials Design (CAMD) at
www.camd.dtu.dk.  

Application
Please submit your online application no later than 15 September 2019 (local time).  Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include: 
  • A letter motivating the application (cover letter)
  • Curriculum vitae
  • Grade transcripts and BSc/MSc diploma
  • Excel sheet with translation of grades to the Danish grading system (see guidelines and Excel spreadsheet here)
Candidates may apply prior to obtaining their master's degree but cannot begin before having received it.

Applications and enclosures received after the deadline will not be considered.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

DTU is a technical university providing internationally leading research, education, innovation and scientific advice. Our staff of 6,000 advance science and technology to create innovative solutions that meet the demands of society, and our 11,200 students are being educated to address the technological challenges of the future. DTU is an independent university collaborating globally with business, industry, government and public agencies.