PhD scholarship in Machine Learning for Molecules - DTU Chemistry
Kgs. Lyngby, Denmark
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DTU - Technical University of Denmark
DTU er et teknisk eliteuniversitet med international rækkevidde og standard. Vores mission er at udvikle og nyttiggøre naturvidenskab og teknisk videnskab til gavn for samfundet.AI has begun to transform molecular discovery and design for proteins, DNA, RNA, small molecules and more. Yet many outstanding challenges in health and sustainability remain data limited. We are offering a PhD scholarship for a student to develop ambitious new machine learning strategies for generating AI-ready data.
You will work at the frontier of active learning and ML-guided experimentation with Asst. Prof. Eli N. Weinstein. Your goal will be to develop fundamental algorithmic techniques to overcome critical bottlenecks on data scale and quality, enabling scientists to gather vastly more information for a given experimental budget.
Efficient active learning depends on the careful co-design of experiments and inference algorithms. You will explore topics such as how to elicit functional priors from billions of years of evolution; how to compress measurements with controlled mixtures of molecules; and how to align models of laboratory experiments with observational human biology. You will draw on ideas from Bayesian optimization and Bayesian deep learning, generative modelling, high throughput screening, and combinatorial synthetic chemistry.
Responsibilities and qualifications
The PhD project will involve both (a) developing foundational probabilistic machine learning methodology, and (b) applied collaboration with experimentalists in chemistry and biology.
The candidate may have degrees in either the natural sciences (chemistry, physics, mathematical/computational biology) or in the formal sciences (statistics, computer science, mathematics), but must have a serious interest in both.
Mathematical maturity and experience with scientific programming are essential. A background in probabilistic methods is highly desirable, at the level of master’s courses in probability, statistical mechanics and/or probabilistic machine learning. You should be willing to take an ambitious and unconventional approach to hard problems and be motivated by a desire for both deep understanding and real-world impact.
You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree.
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 DTU's rules for the PhD education.
Assessment
The assessment of the applicant will be made by Asst. Prof. Eli N. Weinstein.
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 start date will be January 2, 2026, or a mutually agreed alternative. The position is full-time.
You can read more about career paths at DTU here.
Further information
Further information may be obtained from the Head of Section Prof. Esben Thormann esth@kemi.dtu.dk
You can read more about the Chemistry Department at www.kemi.dtu.dk
If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.
Application procedure
Your complete online application must be submitted no later than 28 September 2025 (23:59 Danish time).
Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply now", 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 (in English) including official description of grading scale
- Research sample. Submit a paper or preprint if you have one; otherwise submit a Master’s thesis or other project you are particularly proud of. Add a cover with a short paragraph explaining your contributions.
You may apply prior to obtaining your master's degree but cannot begin before having received it.
Applications received after the deadline will not be considered.
All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply. As DTU works with research in critical technology, which is subject to special rules for security and export control, open-source background checks may be conducted on qualified candidates for the position.
Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear mission to develop and create value using science and engineering to benefit society. That mission lives on today. DTU has 13,500 students and 6,000 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Bayesian Biology Chemistry Computer Science Deep Learning Engineering Machine Learning Mathematics Open Source PhD Physics Research Security Statistics
Perks/benefits: Career development Startup environment
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