The Informatics Institute (IvI) of the University of Amsterdam (UvA) and Janssen R&D Vaccines team up with the vision of using artificial intelligence to improve vaccine design.
The recent corona pandemic with their ever-evolving virus mutations shows the necessity for a fast reliable vaccine development. However, classical exhaustive lab experiments are costly and slow. To overcome such limitations, we want to investigate a data-driven machine learning approach.
To explain a bit, the efficacy of viral vaccines based on spike fusion proteins may depend on the conformation of the spike that is presented to the immune system. Those proteins tend to contain instable parts that might result in an undesired structure of the vaccine immunogen. In this project we want to exploit the recent progress in deep learning methods in combination with big protein data sets to learn to identify and stabilize occurring instable protein regions. Such a trained deep learning model could then quickly suggest vaccine designs that can then be tested in the lab and thus vastly speed up the whole vaccine development process.
For this project we are looking for a PhD candidate who has experience with all the recent major methods in deep learning. The starting date is 1 December 2022 (not flexible). The PhD student will be affiliated with the AI4Science Lab embedded within the Amsterdam Machine Learning Lab (AMLab) of Prof. Max Welling. The research will mainly be carried out at the Informatics Institute of the University of Amsterdam and in collaboration with Janssen researchers.
What are you going to do?
Tasks and responsibilities:
- Apply, invent and evaluate deep learning methodologies for protein data sets;
- Show that these methods have practical consequence in protein stabilization and vaccine design;
- Present your research by contributing to international conferences, workshops, and journals;
- Assist in teaching activities (10% of the time): teaching course tutorials; creating and grading exercises; supervising bachelor and master students, etc.;
- Collaborate with researchers from Janssen;
- Complete a PhD thesis within the appointed duration of four years.
What do you have to offer?
Your experience and profile:
- Master’s degree in Machine Learning, Artificial Intelligence, Deep Learning, Statistics, Computer Science, Mathematics, or a related field;
- Experience in programming and software development. Familiarity with Python and statistical computing libraries (e.g., NumPy, PyTorch, JAX) is preferred;
- Experience with deep learning in general and the following more specific sub-topics: transformers, attention mechanisms, graph neural networks, equivariant neural networks, recurrent neural networks, novelty detection, variational autoencoders, etc.;
- Enthusiasm for our shared vision and the scientific process: formulating and conducting experiments, data collection and analysis, disseminating findings via writing and oral presentations;
- Ability to collaborate and meet with researchers from different disciplines and backgrounds;
- Ability to work effectively in an interdisciplinary field;
- Fluency in English, both written and spoken.
A temporary contract for 38 hours per week for the duration of 4 years (the initial contract will be for a period of 18 months and after satisfactory evaluation it will be extended for a total duration of 4 years). The preferred starting date is as soon as possible. This should lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master students.
The gross monthly salary, based on 38 hours per week and dependent on relevant experience, ranges between € 2,541 to € 3,247 (scale P). This does not include 8% holiday allowance and 8,3% year-end allowance. The UFO profile PhD Candidate is applicable. A favourable tax agreement, the ‘30% ruling’, may apply to non-Dutch applicants. The Collective Labour Agreement of Dutch Universities is applicable.
Besides the salary and a vibrant and challenging environment at Science Park we offer you multiple fringe benefits:
- 232 holiday hours per year (based on fulltime) and extra holidays between Christmas and 1 January;
- Multiple courses to follow from our Teaching and Learning Centre;
- A complete educational program for PhD students;
- Multiple courses on topics such as leadership for academic staff;
- Multiple courses on topics such as time management, handling stress and an online learning platform with 100+ different courses;
- 7 weeks birth leave (partner leave) with 100% salary;
- Partly paid parental leave;
- The possibility to set up a workplace at home;
- A pension at ABP for which UvA pays two third part of the contribution;
- The possibility to follow courses to learn Dutch;
- Help with housing for a studio or small apartment when you’re moving from abroad.
Are you curious to read more about our extensive package of secondary employment benefits, take a look here.
The University of Amsterdam (UvA) is the Netherlands’ largest university, offering the widest range of academic programmes. At the UvA, 30,000 students, 6,000 staff members and 3,000 PhD candidates study and work in a diverse range of fields, connected by a culture of curiosity.
The Faculty of Science has a student body of around 8,000, as well as 1,800 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.
The Amsterdam Machine Learning Lab (AMLab) of Prof. Max Welling conducts research in machine learning, artificial intelligence, and its applications to large scale data domains in science and industry. This includes the development of deep generative models, methods for approximate inference, probabilistic programming, Bayesian deep learning, causal inference, reinforcement learning, graph neural networks, and geometric deep learning.
The AI4Science Lab is embedded within AMLab and is specifically dedicated to the application of recent advances in artificial intelligence, machine learning and deep learning to different fields of sciences, e.g., physics, astronomy, chemistry, biology and life sciences, etc.
Want to know more about our organisation? Read more about working at the University of Amsterdam.
Do you have any questions, or do you require additional information? Please contact:
- Patrick Forré, Assistant Professor.
If you feel the profile fits you, and you are interested in the job, we look forward to receiving your application. You can apply online via the button below. We accept applications until and including 16 October 2022.
Applications should include the following information (all files besides your cv should be submitted in one single pdf file):
- A curriculum vitae, including a list of publications if applicable;
- A research statement describing your interests in the topic;
- A complete record of your courses, including grades and an explanation of the grading system;
- The names and contact information of at least two academic references (please do not include the letters themselves);
- A link to/ a copy of a written work product. Examples: thesis, research paper (working draft or pre-print is acceptable), course project, blog post;
- Optional: A letter providing any additional information not sufficiently highlighted by the other materials. For instance, the letter could include an explanation for a period of poor academic performance.
Please make sure to provide ALL requested documents mentioned above.
You can use the CV field to upload your resume as a separate pdf document. Use the Cover Letter field to upload the other requested documents, including the motivation letter, as one single pdf file.
The interviews will be held in the course of end of October and beginning of November 2022. Please note that the starting date of the position is 1st December 2022 (not flexible).
The UvA is an equal-opportunity employer. We prioritize diversity and are committed to creating an inclusive environment for everyone. We value a spirit of enquiry and perseverance, provide the space to keep asking questions, and promote a culture of curiosity and creativity.
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