Horizon Europe MSCA Doctoral Network PhD scholarship in Computational Proteomics and Machine Learning DTU Biosustain

If you are curious and proactive scientist with expertise and interest in computational biology and data science and you are looking to make a difference working on projects that will have impact on world level challenges this PhD position is for you! The project is supervised by Alberto Santos Delgado at the Technical University of Denmark part (DTU) and co-supervised by Prof. Julios Saez-Rodriguez at the European Bioinformatics Institute (EBI) as part of ProtAIomics a Horizon Europe MSCA Doctoral Network ( In this project we will design a federated knowledge graph framework that facilitates the querying consolidation analysis and interpretation of distributed proteomics-focused clinical knowledge graphs. To achieve this we will employ machine learning techniques to develop local graph representation models which will be aggregated globally to enhance their predictive power and translational relevance all while maintaining strict data privacy standards.

As part of the ProtAIomics MSCA Doctoral Network you will collaborate with top proteomics research scientist and participate in multiple trainings and summer schools. At DTU you will work in an international motivating flexible supportive and friendly environment at a leading research and education institution in Europe.

About the Multi-omics Network Analytics Group
The Multi-omics Network Analytics ( aims to getting a holistic view of biological systems and their context to understand their complexity and provide new insights and applications that can benefit human and environmental health. We focus on Multimodal Data processing and analyzing diverse types such as mass spectrometry (proteomics metabolomics) and metaomics (metagenomics metatranscriptomics metaproteomics) tackling complex biological problems.

A key component is integrating and interpreting multi-omics data using graphs and developing machine learning tools. We apply these technologies to explore and understand complex biological problems spanning human and environmental health.

Further were strong advocates of open science adhering to open principles for our generated data training and software aiming to reduce inequality and promote accessibility by democratizing data science.

Research and Development Opportunities
You will get the opportunity to learn and apply the latest machine learning algorithms/data science methods for clinical proteomics data. Further during the enrollment process you will define together with your supervisors (main and co-supervisor) additional relevant courses from the domains covered in the project (30 ECTS points of relevant PhD courses as required in Danish PhD programs). These courses will ensure that you become a bilingual scientist with deep knowledge in data science as well as biology proteomics computation etc. We anticipate that by working with us you will foster some of the following skills:

• Opportunity to work across multi-disciplinary research areas
• Transferable skills across proteomics data science machine learning and computer science
• Opportunity to tap into an agile innovation ecosystem

Development and application of state-of-the-art machine learning and deep learning on clinical problems

Responsibilities and qualifications
As a PhD student embarking on a three-year journey in proteomics-focused data science and machine learning you will learn leadership project management mentoring and scientific communication. Heres a snapshot of the key responsibilities you will hold:

• Research Project Management: Strategically drive the project from conception through to publication ensuring adherence to scientific and funding objectives.
• Student Supervision: Guide and support students research promoting their academic growth and contributions to the projects success.
• Scientific Dissemination: Actively publish and present research findings enhancing the projects visibility and impact in the scientific community.

Requirements:

• You must have a two-year masters degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year masters degree.
• Proven ability to bridge computational methods (e.g. machine learning) with biological/biomedical domains (e.g. biomarker discovery).
• Experience developing knowledge graphs or integrating heterogeneous omics data.
• Familiarity with ontology-based modelling for integrating heterogeneous data.
• Knowledge of Graph Neural Networks (GNNs) and graph embedding techniques (e.g. using PyTorch Geometric).
• Experience working with MS-based proteomics data and/or other omics data types.
• Familiarity with data preprocessing pipelines for high-throughput omics data (e.g. Nextflow).
• Strong programming skills in Python (Data and Machine Learning stacks).
• Experience with version control and cloud/HPC computing platforms.
• Familiarity with containerization (Docker).
• Ability to collaborate with multidisciplinary teams (e.g. biologists clinicians software engineers) and to communicate complex technical concepts to non-experts.
• Previous experience with federated machine learning is highly valuable though not strictly required.

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 DTUs 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 the PhD salary will be based on the Marie S. Curie compensation scheme conditions and according to the grant agreement. The period of employment is 3 years. Based on seniority the candidate will receive a minimum of DKK 29.70183 (base salary) and 155100 (PhD supplement). In addition DTU will also pay pension consisting of 1807%. Finally it is possible to apply for family allowance

You can read more about career paths at DTU here.

Further information
If you have any questions you are very welcome to contact Alberto Santos at

If you are applying from abroad you may find useful information on working in Denmark and at DTU at DTU Moving to you have the option of joining our monthly free seminar PhDrelocation 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 30 November 2025 (23:59 Danish time) through the DTU system. Additionally to be eligible you must also submit your application via the ProtAIomics portal following the application instructions provided.

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 Experience ( 500 words)
• Scientific Interests ( 500 words)
• Contact details of 2 referees

You may apply prior to obtaining your masters 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 UNs 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 13500 students and 6000 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.