Are you interested in cutting-edge TB vaccine research and advanced data-driven immunology? Then you might be our new PhD student in a 3 -year position.

The project
TB remains a global health emergency and incomplete understanding of protective immunity is a major obstacle for the development of more effective vaccines. Given the complexity of Mtb infection and its mechanisms of evasion to host immunity, a rational vaccine design, rather than an empirical one, is required.

Based on recent scientific advances and preliminary data from our group, you will investigate the hypothesis that effective vaccination induces distinct airway-resident and spatially organised immune states that predict improved infection control, and that a subset of these mechanisms can be captured by translatable biomarker signatures measurable in blood or upper-airway samples.

Using cutting-edge murine models, single-cell transcriptomics, and quantitative spatial imaging, you will deliver reproducible, context- and infection-aware computational analyses of high-dimensional datasets leading to the identification of immune cell states, their spatial organisation, and links to infection outcomes. In parallel, you will prototype a human-supervised AI agent designed to explicitly reason about infection stage, pathogen burden, and host–pathogen immunology to assist scientists in the analysis of multimodal datasets.

While Th1 responses have historically dominated TB vaccine research, we have data showing that our newly developed TB vaccine, H107e/CAF, is able to improve infection control and enhance containment of bacterial growth in preclinical models by inducing Th17 immune responses and orchestrating tissue localization of immune cells. Given that H107e/CAF induces a unique immune response associated with improved outcomes, it is the goal of the project to determine the mechanisms by which these vaccine-mediated responses improve infection control in TB infected lung. We will reach this goal in collaboration with leading research institutions in Europe and US using cutting-edge techniques incl. advanced murine models, single-cell RNA sequencing and multiplex imaging. Insights gained from this project will inform the design of next-generation TB vaccines and support translation of mechanistic findings to human studies.

You will
We are looking for a dedicated student with an interest in infectious disease immunology, vaccines, bioinformatics, and AI. As a PhD student, you will investigate vaccine-induced immune response mechanisms in the TB infected lung using multimodal data, including single-cell transcriptomics, flow cytometry, and confocal microscopy of fixed tissue samples.

The ambition is to understand how vaccination induces Th17-associated immunity and shapes airway-resident and spatially organised immune states that contribute to improved control of TB, and to determine whether these immune features can serve as predictive markers of protection and whether key aspects can be captured as translatable biomarker signatures measurable in blood and/or upper-airway samples. The work will primarily involve computational analysis of single-cell and spatial datasets, including multimodal data integration, alongside experimental data generation in close collaboration with wet-lab teams, as well as manuscript preparation. An integral part of the project is a research stay at one of our collaborating institutions.

Candidate profile
The ideal candidate for the position will feature the following profile:

• Highly motivated student holding a Master’s degree in Bioinformatics, Computational Biology, Biostatistics, or related field
• Strong critical and creative thinking skills
• Self-driven, proactive, and passionate about problem-solving
• Training in statistical and machine learning approaches for complex data analysis (e.g. hypothesis testing, supervised/unsupervised learning, linear models), with interest in foundation models and AI
• Experience with atlas-scale single-cell data analysis, including cell type annotation, differential expression/abundance analysis, etc.
• Training in statistical methods appropriate for single-cell biological research, e.g., sparse data analysis, generative models, batch correction and multi-sample/-modal data integration, etc.
• Proficiency in statistical programming languages such as R and Python for large-scale data analysis
• Experience with image analysis (e.g segmentation, phenotyping, spatial analysis) is an advantage
• Understanding of immunology and experience with wet-lab techniques is a plus
• Comfortable generating and documenting reproducible analyses and workflows
• Dynamic, independent, and goal oriented with a good team spirit

About us
The Department of Infectious Disease Immunology focuses on research and development of next-generation vaccines and diagnostic tools, primarily within tuberculosis (TB), chlamydia, and vaccine adjuvants. The Department conducts both basic and translational research and is highly rated internationally. As part of the SSI Center for Vaccine Research, we can efficiently move products from research into clinical trials. We collaborate closely with a large number of institutions and are externally funded by e.g. the National Institutes of Health, Gates foundation, European Commission and the Danish Research Council.

The Tuberculosis Vaccine Research Group is an integrated part of Novo Nordisk Foundation Initiative for Vaccines and Immunity (NIVI) and is focused on understanding barriers of pulmonary protection and use data from pre-clinical and clinical studies to design novel vaccination strategies. You will be part of a dynamic, international team encompassing scientists, technicians and other students, who are all passionate about global health and TB vaccine research.

We offer
SSI is a workplace internationally recognized for addressing national and global public health challenges. You will become part of an organization with 900 employees carrying out meaningful tasks that strengthen human and animal health through research and preparedness.

Our daily work is characterized by a wide variety of tasks, open doors, and close collaboration with dedicated and highly skilled colleagues. You will have the opportunity for a flexible workday with a good work–life balance, as SSI offers a 37-hour workweek including lunch break, a flexitime scheme, and the possibility of working from home depending on your tasks / flexible planning of working hours (please tailor this to the specific position).

At SSI, we have an active staff and sports association (IK-SERA) offering group training, fitness facilities, a Friday bar, and various social events—and our campus even includes tennis courts and its own childcare facility. SSI is centrally located in Copenhagen, surrounded by green areas with excellent public transport options (bus and metro), and offers free on-site parking.

Are you interested?
Send us your CV and application, even if you do not meet all of our expectations regarding criteria or experience. We kindly ask you not to include a photo in your CV, as we strive for a more inclusive recruitment process with equal opportunities for all applicants.

We expect to hold interviews from week 19.

For further details and informal enquiries please contact Group PI Rasmus Mortensen +45 32 68 8309 / RJM@ssi.dk.

Terms of Employment
The employment is of 3 years duration.

The employment will be in accordance with the terms of the collective agreement between the Ministry of Taxation and the Danish Federation of Professional Associations (AC-overenskomsten) and the Danish Ministry of Taxation’s circular concerning the job structure for scientific staff working with research at sector research institutions (Stillingsstruktur for videnskabeligt personale med forskningsopgaver ved sektorforskningsinstitutioner).

We are looking forward to hear from you.