PhD scholarship in AI Oracles for Fitness Landscape Optimization on Molecular Binders - DTU Health Tech

Are you ready to transform the future of biologics?

Are you passionate about understanding the interplay between AI-based protein design, automation, and cutting-edge data science? And would you like to be part of a newly formed research collaboration between DTU and Novo Nordisk? Then you could be our new Ph.D.-student. Read on to learn more!

About the PhD program - Closed Loop AI-driven Protein Binder Design 
Technical University of Denmark (DTU) and Novo Nordisk have initiated a strategic partnership and created a joint cross-disciplinary research program aimed to tackle one of the life science industry’s biggest challenges: Closed-Loop Design and Optimization of Biologics. 

The research program will build on the recent advances in protein design, automation, and multi-parameter optimization and create a closed loop pipeline able to rapidly design binders to any target and optimized for developability. 

The program is rooted in DALSA (DTU’s Arena for Life Science Automation), a new interdisciplinary center at DTU dedicated to merging life sciences, automation, and data-driven innovation to revolutionize research and development. 

The program combines the expertise of five DTU departments (Construct, Bioengineering, Compute, Electro, and Health Technology) and involves supervisors from both DTU and Novo Nordisk.

What you can expect 
As a PhD student, you will be at the heart of a vibrant and collaborative research environment that includes:

• Fellow PhD students, postdocs, and master’s students working on related projects.
• Expert supervisors and mentors from DTU and Novo Nordisk. The main supervisor is affiliated with DTU Bioengineering, while the co-supervisor is based at Novo Nordisk. This supervisor team ensures the highest level of academic expertise to support both the project and the program.
• Opportunities to participate in conferences, symposia, and networking events to share and enhance your research.

Your role will be pivotal in driving innovation and contributing to a transformative approach to biologics development.

Research project
Recent advancements in generative AI (genAI) have revolutionized the design of molecular binders, particularly within de novo and closed-loop optimization frameworks. By integrating AI-driven methodologies in a closed-loop system, we can iteratively refine binder designs to achieve high-affinity and specificity.

Key components include:

• Generative Models: Utilizing advanced models such as diffusion models to generate an initial set of diverse protein backbones.
• Sequence Refinement: Employing generative tools like ProteinMPNN to explore the sequence space to identify sequences with improved properties.
• Validation: Using AlphaFold2 and other so-called oracles to further enrich the candidate sequences for proteins with proper folding, target interaction, and biophysical properties.
• Optimization: Implementing Design of Experiment and Bayesian optimization techniques to guide sequence selection efficiently to balance exploration and exploitation.

Experimental results from binding assays feed back into the system, enhancing the design process in subsequent iterations. This integrated approach aims to significantly improve the efficiency and success rate of developing high-affinity molecular binders for industrial applications.

Purpose
The purpose of the PhD project is to optimize the process of binder design through closed-loop optimization, emphasizing the efficient achievement of high-affinity and specific binders.

The following research questions will be addressed in this project:

• Create 0-shot oracles (AI models) that can be used to screen sequences and structures from generative models to increase the hit rate.
• Develop biasing and/or training strategies to tune the oracles based on existing experimental data.
• Explore and implement model uncertainty prediction strategies in the oracles.
• Integrate these approaches in a closed loop optimization paradigm.

Qualifications
We are looking for a highly motivated candidate with a master’s degree in Bioinformatics, Computer Science or similar. In particular, we expect the candidate to have expertise on deep learning programming on generative models, language models and/or inverse folding models. In addition, a solid background on protein sequence, structure, and function is required.

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. 

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 
For further information contact Carolina Barra Quaglia (carolet@dtu.dk). 

You can read more about the DTU Health Tech here: www.healthtech.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 9 March 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

You may apply prior to ob­tai­ning your master's degree but cannot begin before having received it. 

The hiring committee consists of representatives from DTU and Novo Nordisk.

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.

About the Novo Nordisk departments where the project will be anchored: Antibody Design Department
Antibody Design Department is part of the Digital Science and Innovation (DSI) area of Research & Early Development at Novo Nordisk, located in Maaloev (Denmark) and London (UK). We use innovative computational tools and techniques to design novel antibodies and VHHs. Our team works collaboratively across various departments, within and outside Research and Early Development, to deliver safe and effective antibody therapies to patients. We value a diverse and inclusive culture, where our team members can thrive and grow. Our team consists of passionate, goal-oriented individuals who take pride in their work and are committed to making a difference in patients' lives.

Automation & Process Optimization
Automation & Process Optimization Department Department is part of the Digital Science and Innovation (DSI) area, which supports the digital transformation across all our therapy areas in Research & Early Development (R&ED) at Novo Nordisk . Automation & Process Optimization Department is located in Maaloev (Denmark). We work in multidisciplinary teams and collaborate with all areas across R&ED to leverage scientific knowledge, partner with our IT organization to ensure access to the most advanced technology platforms and tools and engage in drug development projects across the value chain. Using Bayesian Optimization / Modern Design of Experiment, we build the data-foundation to enable true hybrid development between humans and advanced learning algorithms such as Generative AI.

Novo Nordisk is a leading global healthcare company with a 100-year legacy of driving change to defeat serious chronic diseases. Building on our strong legacy within diabetes, we are growing massively and expanding our commitment, reaching millions around the world and impacting more than 40 million patient lives daily. All of this has made us one of the 20 most valuable companies in the world by market cap. Our success relies on the joint potential and collaboration of our more than 63,000 employees around the world. We recognise the importance of the unique skills and perspectives our people bring to the table, and we work continuously to bring out the best in them.

DTU Health Tech
With a vision to improve health and quality of life through technology, DTU Health Tech engages in research, education, and innovation based on technical and natural science. We educate tomorrow’s health tech engineers and create the foundation for new and innovative services and technologies for the globally expanding healthcare sector with its demands for the most advanced technological solutions. DTU Health Tech’s expertise can be described through five overall research areas: Diagnostic Imaging, Digital Health, Personalised Therapy, Precision Diagnostics, and Sensory and Neural Technology. Our technologies and solutions are developed with the aim of benefiting people and creating value for society. The department has a scientific staff of about 210 persons, 140 PhD Students, and a technical/administrative support staff of about 100 persons of which a large majority contributes to our research infrastructure and related commercial activities.

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.