The University of Luxembourg, a leading international research university, is offering a postdoctoral position in Computational Biology as part of the SinLeigh Consortium. The successful candidate will join the Luxembourg Centre for Systems Biomedicine (LCSB), an interdisciplinary research centre renowned for its work in systems biology and biomedicine, with a particular focus on neurodegenerative diseases such as Alzheimer's and Parkinson's. The LCSB brings together scientists from diverse fields including computer science, mathematics, biology, chemistry, engineering, and physics, fostering a truly interdisciplinary environment. This postdoctoral researcher will be part of the Computational Biology group led by Prof. Antonio del Sol. The group specializes in developing computational models to address challenges in stem cell research, aging, and disease modeling, employing methodologies from mathematics, engineering, and physics, and integrating multiple sources of biological information to study processes at various levels of organization. The SinLeigh Consortium project aims to advance understanding of Leigh syndrome, a severe neurodegenerative disorder, and to explore the therapeutic potential of cannabidiol (CBD) and sildenafil. The postdoc will work within a European consortium of clinicians, biologists, and computational scientists, focusing on generating network models using multi-omics data to uncover regulatory mechanisms involved in disease pathology and therapeutic response. Responsibilities include data harmonization, multi-omics integration, development of network-based models, and analysis to elucidate mechanisms of action. The resulting networks will also be used to identify disease-related pathways that could be targeted by other compounds in a synergistic manner. Applicants must have a Ph.D. in computational biology, bioinformatics, biology, computer science, or related disciplines, with strong computational skills, experience in mathematical modeling and network science, and a strong first-author publication record. Fluency in English is required. Preferred qualifications include prior experience with network-based models in biological systems and publications in bioinformatics or computational biology. The University of Luxembourg offers a modern, dynamic, and international environment, with high-quality equipment and close ties to industry and European institutions. The position is a fixed-term contract for 18 months, full-time (40 hours per week), based at the Belval Campus. The yearly gross salary is EUR 85,176. The university promotes an inclusive culture and encourages applications from individuals of all backgrounds. To apply, candidates should submit their application online via the University of Luxembourg HR system, including a CV, cover letter, transcript of university-level courses, and a list of publications. Early applications are encouraged as they will be processed upon reception. Applications by email will not be considered.

The University of Luxembourg, a leading international research university, is offering a postdoctoral position in Computational Biology at the Luxembourg Centre for Systems Biomedicine (LCSB). The LCSB is renowned for its interdisciplinary research in systems biology and biomedicine, with a particular focus on neurodegenerative diseases such as Alzheimer's and Parkinson's. The centre brings together scientists from diverse fields including computer science, mathematics, biology, chemistry, engineering, and physics, fostering a collaborative environment that advances both fundamental and translational research. The successful candidate will join the Computational Biology group led by Prof. Antonio del Sol. This group specializes in developing computational models to address challenges in stem cell research, aging, and disease modeling. The research leverages methodologies from mathematics, engineering, and physics, integrating multiple sources of biological information to study complex biological processes at various levels of organization. The postdoctoral researcher will participate in a European consortium dedicated to personalizing high-dose glucocorticoid therapy for children with acute immune-mediated diseases. The project involves comparing treatment regimens and identifying multi-omics biomarkers to predict individual treatment response and toxicity. By integrating clinical data, patient-reported outcomes, and multi-omics profiles, the team aims to generate predictive models that guide safer and more effective individualized steroid use. Responsibilities include data harmonization, multi-omics integration, and the development of machine-learning models for patient stratification and outcome prediction. The candidate will also work on integrating complex datasets into clinically actionable biomarkers and decision-support tools to support personalized treatment algorithms. Applicants must have a Ph.D. in computational biology, bioinformatics, biology, computer science, or related disciplines, with strong computational skills and experience in machine learning. A robust first-author publication record in relevant fields and fluency in English are required. Preferred qualifications include prior experience with machine learning approaches in biological systems and additional first-author publications in bioinformatics or computational biology. The University of Luxembourg offers a modern, dynamic, and multilingual environment with high-quality equipment and close ties to industry and European institutions. The position is a fixed-term contract for 18 months, full-time, with a competitive yearly gross salary of EUR 85,176. The university promotes an inclusive culture and encourages applications from individuals of all backgrounds. To apply, candidates should submit their application online via the University of Luxembourg HR system, including a CV, cover letter, transcript of university-level courses, and a list of publications. Early applications are encouraged as review begins upon receipt. For further information, applicants may contact Prof. Dr. Antonio del Sol at [email protected].