PhD fellowship in Machine Learning for Crystallography

PhD fellowship in Machine Learning for Crystallography

Trainee No working from home possible
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At a Glance

  • Tasks: Join an international team to develop machine learning tools for crystallography.
  • Company: University of Copenhagen, part of a dynamic research environment.
  • Benefits: Competitive salary, creative working conditions, and opportunities for international collaboration.
  • Other info: Engage in active research and teaching while pursuing your PhD.
  • Why this job: Make a real impact in pharmaceutical sciences with cutting-edge technology.
  • Qualifications: Master’s degree in physics, chemistry, or nano-science required.

We are offering a three-year PhD fellowship in Machine Learning for Crystallography commencing 1st of September 2026 or as soon as possible thereafter.

Project description: This fellowship forms part of the Novo Nordisk Foundation-funded project "Deep Learning-Accelerated Crystallography Pipeline", a collaboration between University of Copenhagen, Durham University, and the MAX IV synchrotron. You will work closely with an international team of crystallographers, mathematicians, and data scientists. The project seeks to transform small‑molecule structure determination by integrating machine learning algorithms into crystallographic workflows. The successful candidate will contribute to the development of computational tools that will enhance data collection, refinement, and validation. The work will involve simulation of diffraction data, training and testing machine learning models, and integration into an open‑source modular pipeline for high‑throughput crystallography.

Principal supervisor: Associate Professor Anders Østergaard Madsen, Department of Pharmacy

Start: 1 September 2026

Duration: 3 years as a PhD student

Our group and research: You will join a dedicated research team focused on machine learning applications in crystallographic method development and applied crystallography on pharmaceutical systems. The team is part of the research group Pharmaceuticals, Processes and Products at the Department of Pharmacy, and is engaged in the Center for Pharmaceutical Data Science Education. This project involves close collaboration with partners at Durham University (UK) and the MAX IV synchrotron in Lund (Sweden), creating an international research environment. You will work alongside a postdoc and fellow PhD student in Copenhagen, with regular interaction with collaborators in Durham and at MAX IV.

Our department: The mission of the Department of Pharmacy is to advance the pharmaceutical sciences by performing drug-related research and research‑based teaching in topics including pharmaceutical technology and formulation, drug delivery, advanced drug analysis, and clinical and social pharmacy.

Your key tasks as a PhD student at the Faculty of Health and Medical Sciences are:

  • Carrying out an independent research project under supervision
  • Completing PhD courses or equivalent education corresponding to approximately 30 ECTS points
  • Participating in active research environments, including a stay at another research team, preferably abroad
  • Obtaining experience with teaching or other types of dissemination related to your PhD project
  • Teaching of undergraduate students in pharmaceutical sciences
  • Writing a PhD thesis based on your project

Key criteria for the assessment of applicants: Applicants must have qualifications corresponding to a master’s degree related to the subject area of the project, e.g. physics, chemistry, nano‑science. Your master’s degree must be equivalent to a Danish master’s degree (two years). Other important criteria are:

  • Professional qualifications relevant to the PhD project
  • Grade point average achieved
  • Other professional activities
  • A curious mind‑set with a strong interest in crystallography and machine learning

Place of employment: The place of employment is at the Department of Pharmacy, Faculty of Health and Medical Sciences, University of Copenhagen. We offer creative and stimulating working conditions in a dynamic and international research environment. Our research facilities include modern laboratories and computing capabilities.

Terms of employment: The average weekly working hours are 37 hours per week. The position is a fixed‑term position limited to a period of 3 years. The employment is conditioned upon the applicant’s successful enrolment as a PhD student at the Graduate School at the Faculty of Health and Medical Sciences, University of Copenhagen. This requires submission and acceptance of an application for the specific project to the Graduate School of Health and Medical Sciences. The PhD study must be completed in accordance with The Ministerial Order on the PhD programme (2025) and the Faculty’s rules on achieving the degree. The PhD student is expected to be affiliated to the graduate programme in pharmaceutical sciences, Drug Research Academy. Salary, pension, and terms of employment are in accordance with the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State. Depending on seniority, the monthly salary starts at approximately 31,600 DKK (roughly 4,200 EUR as of April 2026) plus pension.

Application procedure: Your application, in English, must be submitted electronically and must include the following documents in PDF format:

  • Motivated letter of application (max. one page)
  • CV including education, experience, language skills and other skills relevant for the position
  • Certified copy of original Master of Science diploma and transcript of records in the original language, including an authorized English translation if issued in a language other than English or Danish. If not completed, a certified/signed copy of a recent transcript of records or a written statement from the institution or supervisor is accepted. As a prerequisite for a PhD fellowship employment, your master’s degree must be equivalent to a Danish master’s degree. Applicants with a Master’s degree from abroad should also enclose a short description of the grading scale used.
  • References and recommendations (if possible)

The deadline for applications: 3 June :59 CET. We reserve the right not to consider material received after the deadline, and not to consider applications that do not meet the above requirements. The University of Copenhagen welcomes all qualified candidates, regardless of personal background.

PhD fellowship in Machine Learning for Crystallography employer: Københavns Universitet

The University of Copenhagen offers an exceptional environment for aspiring researchers, particularly in the PhD fellowship in Machine Learning for Crystallography. With access to cutting-edge research facilities and a collaborative international team, employees benefit from a dynamic work culture that fosters creativity and innovation. The university prioritises professional development, providing opportunities for teaching and engagement in active research environments, making it an ideal place for those seeking meaningful and rewarding academic careers.

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Contact Details:

Københavns Universitet Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land PhD fellowship in Machine Learning for Crystallography

Tip Number 1

Network like a pro! Reach out to current PhD students or faculty members in the Department of Pharmacy. They can give you insider info about the programme and might even put in a good word for you.

Tip Number 2

Prepare for your interview by brushing up on your machine learning and crystallography knowledge. Be ready to discuss how your skills can contribute to the project. We want to see your passion!

Tip Number 3

Showcase your curiosity! During interviews, share examples of how you've tackled complex problems in the past. This will highlight your strong interest in both crystallography and machine learning.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who follow instructions!

We think you need these skills to ace PhD fellowship in Machine Learning for Crystallography

Machine Learning
Crystallography
Data Simulation
Model Training and Testing
Computational Tool Development
Open-source Software Integration
Research Methodology

Some tips for your application 🫡

Craft a Compelling Motivated Letter:Your motivated letter is your chance to shine! Make sure to express your passion for machine learning and crystallography, and how your background aligns with the project. Keep it concise, ideally one page, and let your enthusiasm show!

Showcase Your CV:Your CV should highlight all relevant education and experience. Don’t forget to include any skills that relate to the PhD project, like programming languages or research techniques. We want to see what makes you stand out!

Get Your Documents in Order:Make sure you have all the required documents ready in PDF format. This includes your Master’s diploma, transcripts, and any references. Double-check everything to avoid any last-minute hiccups!

Apply Through Our Website:Don’t forget to hit that 'Apply now' button on our website! It’s the easiest way to submit your application and ensures it gets to the right place. We can’t wait to see what you bring to the table!

How to prepare for a job interview at Københavns Universitet

Know Your Stuff

Make sure you brush up on your knowledge of machine learning and crystallography. Familiarise yourself with the latest research and techniques in these fields, especially those related to the project. Being able to discuss recent advancements will show your genuine interest and expertise.

Show Your Collaborative Spirit

Since this role involves working closely with an international team, be prepared to discuss your experience in collaborative projects. Share examples of how you've worked effectively with others, particularly in diverse teams, and highlight your communication skills.

Prepare Thoughtful Questions

Interviews are a two-way street! Prepare insightful questions about the project, the team dynamics, and the research environment. This not only shows your enthusiasm but also helps you gauge if this is the right fit for you.

Demonstrate Your Curiosity

A curious mindset is key for this PhD fellowship. Be ready to talk about what excites you about crystallography and machine learning. Share any personal projects or experiences that reflect your passion and willingness to learn.