Postdoc in Computational Systems Biology and Metabolic Modeling

INSELSPITAL; Bern; Vor Ort; Vertraulich; Vollzeit

Benefits dieser Stelle

Collaborative research environment

Professional development opportunities

Access to large biomedical datasets

Zusammenfassung

Inselspital, Bern University Hospital, is seeking a researcher to develop and apply mathematical and ML models to complex biological datasets, including multi-omics data. You will work on metabolic network reconstruction and validation using experimental data, contributing to multidisciplinary projects and scholarly publications.

The role offers a collaborative, state‑of‑the‑art research environment with opportunities for scientific and professional development in metabolism, systems biology,

Qualifikationen

• PhD or equivalent in computational biology, systems biology, applied mathematics, biochemical engineering, or a related field.
• Strong expertise in mathematical and statistical modelling, machine learning, and systems biology with high‑dimensional data experience.
• Experience in in silico metabolic modelling, network reconstruction or data‑driven simulation.

Aufgaben

• Develop and apply mathematical, statistical and ML models to complex biological data.
• Reconstruct and validate tissue‑specific metabolic networks with experimental data.
• Collaborate in multidisciplinary research projects and communicate results internally and at conferences.

Kenntnisse

Mathematical modelling

Statistical modelling

Machine learning

Systems biology

R

Python

MATLAB

Ausbildung

PhD or equivalent in computational biology/related field

Jobbeschreibung

What you can expect

• Develop and apply mathematical, statistical, and machine-learning models to complex, high-dimensional, and multimodal biological and clinical datasets, including spatial and imaging data
• Model lipid and nutrient metabolism using compartmental, kinetic, mechanistic, metabolic network, or physiologically based approaches
• Reconstruct and model tissue-specific metabolic networks and validate model predictions using experimental data
• Participate in and contribute to multidisciplinary and collaborative research projects.
• Prepare, present, and communicate scientific findings at internal meetings, international conferences, and through peer-reviewed publications

Your Profile

• PhD or equivalent in computational biology, systems biology, applied mathematics, biochemical engineering, or a related field
• Strong expertise in mathematical and statistical modelling, machine learning, and systems biology, with experience analysing high-dimensional, multimodal, or multi-omics biological or clinical data
• Demonstrated experience in in silico metabolic modelling, e.g. constraint-based or genome-scale metabolic modelling, metabolic network reconstruction, kinetic or metabolic flux modelling, or data-driven simulation
• Proficiency in R, Python, or MATLAB and experience integrating experimental data with computational models;
• Experience in mass spectrometry, spatial omics, molecular imaging, or tissue imaging is a strong asset
• Enthusiastic and collaborative scientist with strong analytical and problem-solving skills, the ability to work independently and in multidisciplinary teams, and excellent written and spoken English

What we offer

• A supportive, collaborative, and state-of-the-art research environment with opportunities for scientific and professional development
• Participation in multidisciplinary research projects at the interface of computational biology, systems biology, metabolism, multi-omics, molecular imaging, and clinical research
• The opportunity to work with large datasets from pre-clinical and clinical studies
• Close collaboration with experts from different scientific and clinical disciplines

With the Inselspital, Bern University Hospital, the hospitals Riggisberg, Aarberg, Belp and the Bern Rehabilitation Center Heiligenschwendi, the Insel Gruppe forms the largest full-service medical care system in Switzerland, from cutting‑edge medicine to primary care. More than 11,000 employees from 102 nations ensure that our patients are treated according to the latest developments, methods and possibilities in medicine.