PhD fellowship in Machine Learning for Crystallography in North East

PhD fellowship in Machine Learning for Crystallography in North East

North East Trainee 30000 - 40000 € / year (est.) No home office 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 teaching and research.
  • Other info: Collaborate with top researchers and gain valuable experience in a global setting.
  • Why this job: Make a real impact in pharmaceutical sciences with cutting-edge technology.
  • Qualifications: Master's degree in physics, chemistry, or related fields required.

The predicted salary is between 30000 - 40000 € per year.

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

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

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.

Job description: 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 by clicking “Apply now” below 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 2026 23:59 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.

Info: Employment start: 01-09-2026. Working hours: Full time. Department/Location: Department of Pharmacy.

PhD fellowship in Machine Learning for Crystallography in North East employer: Københavns Universitet

The University of Copenhagen offers an exceptional environment for aspiring researchers through its PhD fellowship in Machine Learning for Crystallography. With a focus on innovative research and collaboration within an international team, employees benefit from modern facilities, a dynamic work culture, and ample opportunities for professional growth in the pharmaceutical sciences. The university's commitment to advancing knowledge and fostering creativity makes it an ideal employer for those seeking meaningful and impactful careers.

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Contact Detail:

Københavns Universitet Recruiting Team

StudySmarter Expert Advice🤫

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

Tip Number 1

Network like a pro! Reach out to current PhD students or faculty members in the crystallography and machine learning fields. They can provide insider info about the application process and might even put in a good word for you.

Tip Number 2

Prepare for interviews by brushing up on your technical knowledge and research interests. Be ready to discuss how your background aligns with the project goals, especially around machine learning applications in crystallography.

Tip Number 3

Show your passion! When you get the chance to chat with potential supervisors or team members, express your enthusiasm for the project and how you see yourself contributing to the research.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re serious about joining our dynamic research environment.

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

Machine Learning
Crystallography
Data Simulation
Model Training and Testing
Computational Tool Development
High-Throughput Crystallography
Research Methodology

Some tips for your application 🫡

Craft a Motivated Letter:Your motivated letter is your chance to shine! Keep it concise, ideally one page, and make sure to express your passion for machine learning and crystallography. Highlight how your background aligns with the project and why you want to join our team.

Show Off Your CV:Your CV should be a snapshot of your academic journey and relevant experiences. Include your education, any research projects, and skills that relate to the PhD fellowship. Remember, we want to see what makes you unique!

Get Your Documents Ready:Make sure you have all the required documents in PDF format. This includes your Master’s diploma, transcripts, and any references. If your documents are in another language, don’t forget to include an English translation!

Apply Through Our Website:When you're ready, 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. Don’t miss the deadline – we can’t wait to hear from you!

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 in these fields, especially any recent advancements related to the project. This will not only show your genuine interest but also help you engage in meaningful discussions during the interview.

Showcase Your Experience

Prepare to discuss your previous projects or research that relate to the PhD fellowship. Highlight any experience you have with data collection, simulation, or machine learning models. Be ready to explain how your background aligns with the goals of the project and how you can contribute to the team.

Ask Thoughtful Questions

Interviews are a two-way street! Prepare some insightful questions about the research environment, collaboration opportunities, and the specific challenges the team is facing. This demonstrates your enthusiasm for the role and helps you assess if the position is the right fit for you.

Be Yourself

While it's important to be professional, don't forget to let your personality shine through. The interviewers want to see if you'll fit into their team dynamic. Share your passion for crystallography and machine learning, and don’t hesitate to express your curiosity and eagerness to learn.