⛔ This position is no longer available.
University: University of Basel
Country: Switzerland
Deadline: Not specified
Fields: Computational Biology, Bioinformatics, Applied Mathematics, Biomedical Engineering, Statistics
Are you eager to advance your expertise in computational biology while contributing to pediatric healthcare innovations on a global scale?
Switzerland continues to be a beacon for world-class research and academic excellence, offering unique opportunities for ambitious scholars. The University of Basel, one of Europe’s oldest and most esteemed universities, is inviting applications for a fully funded PhD position in Computational Biology within its Department of Biomedical Engineering. This position is ideal for candidates passionate about leveraging quantitative methods to answer pressing biomedical questions and seeking to make a tangible impact on child health worldwide.
About the University or Research Institute
Founded in 1460, the University of Basel is Switzerland’s oldest university and a pillar of academic tradition and innovation. Located in the vibrant city of Basel, the university is recognized for its commitment to research-driven education, fostering an environment where curiosity, diversity, and collaboration thrive. The Department of Biomedical Engineering, situated within the Faculty of Medicine, is at the forefront of translating fundamental scientific discoveries into practical medical solutions. The university’s strong ties with renowned research centers such as the Basel Research Centre for Child Health (BRCCH), the University Children’s Hospital Basel (UKBB), and the Swiss Tropical and Public Health Institute (Swiss TPH) provide students with access to a dynamic, interdisciplinary academic community.
Switzerland itself is known for its high quality of life, safety, and multicultural environment. As a hub for international research and innovation, the country offers outstanding infrastructure, generous funding for science, and a welcoming atmosphere for scholars from around the world. Living and studying in Basel means benefiting from the city’s rich cultural life, excellent public transportation, and proximity to other major European centers.
Research Topic and Significance
The core focus of this PhD position is the development and application of advanced mathematical and computational models to understand how early-life exposures to the microbiome influence the developing immune system and shape lifelong health outcomes. This research is situated at the intersection of systems biology, mathematical modeling, and pediatric medicine.
Understanding the complex interplay between the microbiome and immune system during early childhood is essential for deciphering the roots of infectious diseases, vaccine responses, and non-communicable diseases. The insights gained from this work have the potential to inform actionable strategies for pediatric care and public health, particularly in the context of global health disparities. By integrating mechanistic modeling, causal inference, and machine learning with longitudinal multi-omics data from diverse pediatric cohorts, the project aims to unravel the biological mechanisms underlying health trajectories and disease susceptibility from infancy onwards.
Project Details
The successful candidate will join the Pediatric Disease Modeling Lab, an interdisciplinary research group dedicated to quantitative approaches in pediatric health. The lab’s mission is to bridge basic science and clinical application, translating complex biological data into knowledge that can inform healthcare strategies. The research team collaborates closely with clinical and experimental partners, both locally and internationally, providing an enriching environment for scientific growth.
The PhD student will have the opportunity to work with unique longitudinal datasets from international pediatric cohorts, employing state-of-the-art methods in mathematical modeling, statistical analysis, and machine learning. The role involves integrating and analyzing multi-omics data, developing and parameterizing mechanistic models, and collaborating with a network of experts in computational biology, immunology, and global health. The position offers strong mentorship, opportunities for career development, and participation in the university’s PhD program in Biomedical Engineering.
Candidate Profile
This position is suited for highly motivated individuals with a strong quantitative background and a keen interest in biomedical research. Ideal applicants will have:
– A Master’s degree in Computational Biology, Bioinformatics, Applied Mathematics, Physics, Statistics, Computer Science, Engineering, or a related quantitative field.
– Demonstrated interest in applying quantitative and computational methods to biological or medical questions.
– Experience with programming languages such as Python, R, or MATLAB.
– Excellent written and spoken communication skills in English.
– Motivation to work in an international, interdisciplinary research environment.
Additional desirable qualifications include experience with statistical or mechanistic modeling, machine learning, and familiarity with biological data analysis (e.g., microbiome, transcriptomics, or immunological data). A background in dynamical systems, Bayesian inference, causal inference, or an interest in global health, immunology, or developmental biology will be advantageous.
The University of Basel values diversity and inclusion, ensuring equal opportunities and fostering a respectful, supportive team culture.
Application Process
The position is available from August 1, 2026, or later by mutual agreement. Applications will be reviewed on a rolling basis until the position is filled. Interested candidates should submit their application via the University of Basel Recruiting-Portal, including:
– A cover letter describing research interests and motivation
– A complete curriculum vitae
– Contact details of at least two references willing to provide recommendation letters upon request
For further details and to submit your application, please visit the official job posting at:
https://jobs.unibas.ch/offene-stellen/phd-position-in-computational-biology/5d6e97bb-0881-48b3-83fb-9a9d7e48d63c
Conclusion
This PhD position at the University of Basel offers an outstanding platform for aspiring computational biologists to advance their skills, contribute to impactful research, and collaborate within a world-class academic network. If you are passionate about the intersection of computational science and pediatric health, and eager to make a difference through innovative research, you are encouraged to apply. For more opportunities like this, follow similar announcements and stay engaged with the latest in biomedical research.
Questions & Answers
Question: What makes Switzerland an attractive destination for PhD studies in computational biology?
Switzerland offers a high standard of living, excellent research infrastructure, and a strong culture of innovation. The country’s universities are internationally renowned, and students benefit from multicultural environments, generous funding, and opportunities for international collaboration.
Question: What kind of research environment can I expect at the University of Basel?
The University of Basel provides a collaborative, interdisciplinary research environment with access to leading clinical and research institutions. Students are supported by experienced mentors and have opportunities for professional development and networking.
Question: What skills are most important for success in this PhD position?
A strong quantitative background, programming proficiency, and an interest in applying mathematical models to biological questions are essential. Effective communication and teamwork skills, as well as motivation to work in an international context, are also critical.
Question: How should I prepare my application for this position?
Your application should clearly demonstrate your research interests, motivation, and relevant experience. Be sure to include a well-structured cover letter, a comprehensive CV, and contact details for at least two references.
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