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Are you passionate about building the AI systems that will power the next generation of cancer immunotherapy? Do you want to push the boundaries of generative protein design, protein language models, and active learning to solve one of the most challenging specificity problems in computational biology? We are looking for a computationally oriented PhD candidate to join an ambitious Novo Nordisk Foundation-funded collaboration between the Digital Biotechnology Lab (Assoc. Prof. Timothy P. Jenkins, DTU Bioengineering) and the T Cells and Cancer group (Prof. Sine Reker Hadrup, DTU Health Technology).
About the position
This is a computational and AI methods-focused PhD. The project centres on building the algorithmic and modelling infrastructure needed to design highly specific de novo
protein minibinders (miBds) that target peptide-MHC complexes (pMHC) for use in next-generation CAR-T cell immunotherapy. pMHC complexes present intracellular tumour antigens on the surface of cancer cells and are the natural recognition target for T cells. Our groups recently demonstrated proof-of-concept in Science
(2025) that AI-designed miBds can functionally replace T cell receptors in CAR-T cell constructs. The key bottleneck now is specificity: ensuring miBds bind their intended pMHC target with minimal cross-reactivity to unrelated pMHC complexes or off-target proteins. Solving this computationally is the core challenge of this PhD.
You will build and own the computational platform at the heart of this project. This means working across the full generative design stack: running and adapting diffusion-based structure generation models (RFdiffusion, RFdiffusion2, BoltzDesign), applying protein language models (ProteinMPNN, ESM) for sequence design and scoring, and building hallucination and filtering pipelines to identify high-confidence candidates from large in silico libraries. You will develop active learning strategies that route experimental effort intelligently, feeding binding and specificity data from collaborators in Prof. Hadrup’s group back into the design loop to refine subsequent generations of miBds. The successful candidate will be the architect of the computational platform underpinning the entire project.
Responsibilities and qualifications
- Design and generate structurally diverse miBd libraries using diffusion-based structure generation models (RFdiffusion, RFdiffusion2, BoltzDesign) and protein language model-guided sequence design (ProteinMPNN, ESM variants).
- Develop hallucination and multi-stage filtering pipelines to identify high-confidence binder candidates from large in silico libraries, integrating predicted structure quality, interface metrics, and sequence diversity.
- Build active learning strategies to select which candidates to validate experimentally, maximising information gained per design-test cycle.
- Develop and apply fast computational models for in silico cross-reactivity panning across diverse pMHC sequence spaces and proteome-wide off-target interaction screening.
- Integrate experimental binding fingerprint and specificity data from collaborators into model training and refinement loops, iterating predictions with each new dataset.
- Explore emerging protein design paradigms including flow matching, all-atom models, and structure-conditioned language models as the field evolves.
- Publish results in high-impact peer-reviewed journals and present findings at international conferences.
- Contribute to teaching and mentoring activities within the Digital Biotechnology Lab.
- A strong background in deep learning or generative modelling, with demonstrable project or research experience.
- Proficiency in Python and familiarity with at least one deep learning framework (PyTorch, JAX, or similar).
- Excellent analytical skills and comfort working with open-ended, research-stage problems.
- Strong communication skills and a genuinely collaborative approach to interdisciplinary science.
- Hands-on experience with generative protein design tools: diffusion models (RFdiffusion), structure prediction (AlphaFold, Boltz), or protein language models (ESM, ProteinMPNN).
- Experience with active learning, experimental design, or reinforcement learning applied to scientific problems.
- Familiarity with protein structure, sequence representations, or structural bioinformatics.
- Knowledge of immunology or antigen presentation at a conceptual level.
- Experience with high-performance or GPU-accelerated computing workflows.
You must have:
- A strong background in deep learning or generative modelling, with demonstrable project or research experience.
- Proficiency in Python and familiarity with at least one deep learning framework (PyTorch, JAX, or similar).
- Excellent analytical skills and comfort working with open-ended, research-stage problems.
- Strong communication skills and a genuinely collaborative approach to interdisciplinary science.
It would further be beneficial if you have:
- Hands-on experience with generative protein design tools: diffusion models (RFdiffusion), structure prediction (AlphaFold, Boltz), or protein language models (ESM, ProteinMPNN).
- Experience with active learning, experimental design, or reinforcement learning applied to scientific problems.
- Familiarity with protein structure, sequence representations, or structural bioinformatics.
- Knowledge of immunology or antigen presentation at a conceptual level.
- Experience with high-performance or GPU-accelerated computing workflows.
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
We will assess candidates primarily on the basis of their academic track record and depth of experience in machine learning, generative modelling, or computational biology. Demonstrated ability to develop and apply AI methods to real scientific problems, and genuine motivation for the specific challenges of this project, will be weighted heavily. Shortlisted candidates will be invited to interview on a rolling basis.
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.
Start date will be 1 September 2026, or as soon as possible thereafter.
You can read more about the Digital Biotechnology Lab at www.digital-biotechnology.com and career paths at DTU here .
Further information
Further information may be obtained from Assoc. Prof. Timothy P. Jenkins (tpaje@dtu.dk).
You can read more about the Digital Biotechnology Lab at www.digital-biotechnology.com and DTU Bioengineering at www.bioengineering.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 19 May 2026 (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.
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.
This position is part of an NNF Interdisciplinary Synergy Programme grant (2026–2030, ~19.5 MDKK) awarded to Prof. Sine Reker Hadrup and Assoc. Prof. Timothy P. Jenkins, focused on developing AI-designed pMHC minibinders as next-generation T cell targeting modules for cancer immunotherapy. The successful candidate will join the Digital Biotechnology Lab at DTU Bioengineering, which is recognised as one of Europe’s leading centres for AI-driven protein binder discovery.
DTU – For the benefit of society since 1829
DTU is one of Europe's leading elite technical universities. Through research and education at an international top level, we create solutions to the major societal challenges of our time and help secure Europe's global leadership in sustainable technological development. Since Hans Christian Ørsted founded DTU almost 200 years ago, our mission has remained the same: We develop and create value through the natural and technical sciences for the benefit of society. DTU has 13,800 students, 1,600 PhD students, and 6,500 employees. We work in an international environment and have an inclusive, stimulating, and informal work culture. DTU has campuses in all parts of Denmark and in Greenland and collaborates with the best universities around the world.
About the research project
The position is funded by the Independent Research Fund Denmark (DFF-Research Project 1, FNU) and is part of a research programme investigating how microglial states emerge during development and how the same regulatory logic shapes microglial behaviour and neuronal vulnerability.
The successful candidate will lead the computational and integrative arm of a project on the epigenetic and transcriptomic drivers of microglial ontogeny in early brain development. This includes constructing high-resolution single-cell transcriptomic and chromatin atlases of microglia, inferring regulatory networks underlying lineage diversification, and integrating these maps with spatial and perturbation datasets generated in the laboratory.
The role is anchored in the developmental programme but extends across the wider laboratory, which has generated single-cell, single-nucleus, and spatial multi-omics resources spanning disease models, multiple brain regions, developmental and aging stages, and key genetic perturbations. The successful candidate will have access to these datasets and is expected to contribute computational leadership across linked projects within the lab.
Your job responsibilities
As a Postdoc, your position is primarily research-based but may also involve limited teaching assignments. You will contribute to the development of the department through research of high international quality.
Your main tasks will consist of:
- Independent research of high international quality, including publication
- Computational analysis and integration of large-scale single-cell, single-nucleus, and spatial omics datasets
- Development of analytical or quantitative approaches to study cell-state transitions, lineage relationships, and regulatory programmes
- Close collaboration with experimental researchers within the laboratory and with external partners
- Contribution to manuscript preparation, grant applications, and dissemination of results
Your competences
You have academic qualifications at the PhD level in computational biology, bioinformatics, systems biology, neuroscience, or a related field.
In addition, we expect:
- Strong experience with single-cell and/or spatial omics data analysis
- Proficiency in Python and/or R and modern data analysis workflows
- A track record of independent first-author research
- Ability to work independently and collaboratively in an interdisciplinary environment
- Strong written and spoken English
- Experience with multi-modal data integration (e.g., scRNA-seq with scATAC-seq or spatial data)
- Background in lineage tracing, developmental biology, or cell-state modelling
- Familiarity with regulatory network inference or chromatin analysis
- Interest in neurobiology, immunology, or neurodegenerative disease
- Familiarity with mouse models; FELASA certification is welcome but not required
Shortlisting will be used.
Questions about the position
If you have any questions about the position, please contact Associate Professor Dong Won Thomas Kim (tkim@dandrite.au.dk).
Your place of work will be the Department of Biomedicine, Høegh-Guldbergs Gade 10, DK-8000 Aarhus C, Denmark.
We expect to conduct interviews in June 2026.
DANDRITE
The Danish Research Institute of Translational Neuroscience (DANDRITE) is the Danish node of the Nordic EMBL Partnership for Molecular Medicine and is hosted by Aarhus University and funded by the Lundbeck Foundation. DANDRITE is devoted to interdisciplinary approaches in basic and translational neuroscience and is placed at two departments: Department of Biomedicine (Faculty of Health) and Department of Molecular Biology and Genetics (Faculty of Natural Sciences).
The organization and environment stimulate for genuine convergent research of natural sciences, engineering, and medicine - including also clinical research projects together with researchers from Aarhus University Hospital. The association to the European Molecular Biology Laboratory (EMBL) facilitates collaborative research, access to scientific infrastructure, and fosters innovative international research talent. You can read more about DANDRITE here and about the faculty here.
The Department of Biomedicine
The Department of Biomedicine prioritises diversity and a good work environment, as this is a prerequisite for groundbreaking research. In a diverse and international research environment, dedicated employees are looking to generate new knowledge within biomedical research areas such as infection and inflammation, membranes, neuroscience and personalised medicine. The Department of Biomedicine provides research-based teaching of the highest quality and is responsible for a large part of the medical degree programme. Academic staff contribute to the teaching. English is the preferred language in the laboratory, at meetings and at seminars. The department employs approx. 500 people from all over the world, and they make use of the department's modern laboratory-, core- and animal facilities. The Department of Biomedicine focuses on innovation, entrepreneurship and collaboration with business and industry, and numerous researchers from the department have established companies to develop new medicinal treatments founded in professional scientific basic research. You can read more about the department here and about the faculty here.
Terms of employment
- Appointment as a postdoc requires academic qualifications at PhD level.
- Further information on the appointment procedure can be found in the Ministerial Order on the Appointment of Academic Staff at Universities.
- The appointment is in accordance with the Danish Confederation of Professional Associations (Akademikerne).
- Remuneration is in accordance with the above, and the Salary agreement catalogue for staff at Health.
- The yearly base salary for a fulltime postdoc is between DKK 484.214,84 and DKK 538.720,20 depending on the years of working experience after achieved MSc degree. The base salary includes a position related supplement and pension (17.1 %). Additional supplement(s) for special qualifications can be negotiated. Authorisation supplemement(s) will be granted, if relevant for the position. Your local eligible trade union representative at Aarhus University negotiates your salary on your behalf.
- Researchers recruited from abroad are offered a special researcher tax scheme with a lower tax rate.
- Further information on qualification requirements and job description can be found in the Ministerial Order on Job Structure for Academic Staff
Application
Your application must include the following:
- Motivated application
- Curriculum Vitae
- Diploma
- Template for applicant - postdoc
- A list of publications
- A teaching portfolio. We refer to Guideline on the use of teaching portfolios
- A maximum of five of the publications of greatest relevance to the job may be submitted (optional)
- Research plan can be uploaded (optional)
- Coauthor statement(s) can be uploaded (optional)
- References/recommendations can be uploaded separately in the e-recruitment system (optional)
Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants.
International applicant?
Aarhus University offers a broad variety of services for international researchers and accompanying families, including assistance with relocation and career counselling to expat partners. Please find more information about the International Staff Office and the range of services here. Aarhus University also has a Junior Researcher Association and offers career development support. You can read more about these resources here.
The application must be submitted via Aarhus University’s recruitment system, which can be accessed under the job advertisement on Aarhus University's website.
Aarhus University
Aarhus University is an academically diverse and research-intensive university with a strong commitment to high-quality research and education and the development of society nationally and globally. The university offers an inspiring research and teaching environment to its 37,000 students (FTEs) and 8.700 employees and has an annual revenue of EUR 1.106 billion. Learn more at www.international.au.dk/
En tant que Site Supervisor en électricité, tu joues un rôle de premier plan dans la coordination des activités d’un site technique.
🔧 Opération & Technique
- Organiser et coordonner les activités d’une équipe de 10 techniciens : planning, répartition des tâches, accompagnement quotidien.
- Établir des diagnostics de pannes complexes et garantir des interventions de qualité.
- Suivre et valider les prestations sur le terrain, contrôler la qualité des interventions.
- Gérer les stocks de matériel et suivre les commandes techniques.
- Participer aux audits techniques et accompagner les équipes pendant ceux-ci.
📝 Reporting & communication
- Rédiger des rapports d’intervention clairs et complets.
- Assurer la communication avec le client, participer aux réunions de suivi.
- Transmettre les mises à jour techniques à l’équipe et au service interne.
- Formation : Bachelier technique (ou expérience équivalente).
- Expérience : Minimum 5 ans dans un rôle technique, avec une première expérience réussie en management d’équipe.
Compétences techniques :
- Maîtrise des installations électriques basse, moyenne et haute tension.
- Capacité à diagnostiquer et résoudre des pannes complexes.
Langues : Français courant. L’anglais est un atout.
Certificats : VCA, BA4/BA5 souhaités.