PhD Scholarships (2) in Machine Learning: Uncertainty Quantification for Graph Neural Networks – DTU Compute

Job Description

Do you want to do research on cutting edge machine learning methods? If you are establishing a career as a researcher in machine learning, and your dream is to work with computational drug discovery or molecular data science, we can offer you the best possible foundation.  We seek two highly motivated and talented PhD students to join our group at DTU Compute, and we offer funded PhD scholarships (3 years employment) in a vibrant interdisciplinary research environment.

Project description In the coming years, machine learning is expected to revolutionize molecular discovery and design. The traditional cycle of screening, simulation, and synthesis will be enhanced by automated, data driven, high-throughput screening, capable of predicting the function of novel compounds. Deep neural networks are the pivotal machine learning technology that enables these advancements. In particular, the recently developed graph convolutional neural networks show outstanding results. A central scientific challenge is to search the vast space of potential molecules, and the state-of-the-art is uncertainty guided search; however, current neural networks lack precise and calibrated uncertainty estimates. Our goal is to create novel methods for uncertainty quantification in graph neural networks, for example by advancing techniques such as variational approximation, ensembles, Monte Carlo sampling, and post-calibration.

Responsibilities During the PhD program, you are expected to:

  • Work with state-of-the-art graph nerual network (GNN) architectures for molecular data.
  • Develop novel methods for uncertainty quantification in GNNs.
  • Publish scientific papers and present research results in top machine learning conferences such as NeurIPS, ICML, UAI, and AISTATS. 
  • Assist in machine learning teaching and supervision.

Qualifications Candidates should have the following required skills:

  • Proven experience with implementing machine learning methods in Python and Pytorch/Tensorflow. 
  • Proven experience in probabilistic modeling, probability theory and/or statistics.
  • High level of motivation and creative problem solving skills. 
  • Excellent communication and writing skills in English. 

It is an added benefit if you have experience with graph neural networks, molecular modelling, or computational chemistry.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.

Applicable for all scholarshipsApproval and Enrolment The scholarships for the PhD degree are subject to academic approval, and the candidates 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 applicants will be made by Associate Professor Mikkel N. Schmidt.

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.You can read more about career paths at DTU here.  

Further information Further information may be obtained from Mikkel N. Schmidt, / You can read more about DTU Compute at 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 18 June 2023 (Danish time). Interviews are held continuously. 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

Incomplete applications will not be considered. 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.

DTU Compute DTU Compute is a unique and internationally recognized academic department with 385 employees and 11 research sections spanning the science disciplines mathematics, statistics, computer science, and engineering. We conduct research, teaching and innovation of high international standard – producing new knowledge and technology-based solutions to societal challenges. We have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), internet of things (IoT), smart and secure societies, smart manufacturing, and life science. At DTU Compute we believe in a diverse workplace with a flexible work-life balance.

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.