SNSF-funded scientific research position in chemometrics or computational biology

Poste de recherche scientifique financé par le SNSF en chimie. Opportunité de travailler sur des projets innovants dans un environnement de recherche dynamique.

Tâches

• Développer des pipelines computationnels pour analyser les lipides.

• Utiliser des outils de chimie informatique pour prédire des structures.

• Intégrer des données multi-omiques avec des modèles métaboliques.

Compétences

• Doctorat ou Master avec 5 ans d'expérience en biologie computationnelle.

• Compétence en programmation (R, MATLAB, Python) requise.

• Expérience en analyse de spectres de spectrométrie de masse.

Dysregulation of lipid metabolism plays a key role in development and progression of metabolic disorders including obesity, type 2 diabetes and metabolic dysfunction-associated steatotic liver disease (MASLD). We are seeking a highly motivated scientist with strong background in chemistry and expertise in mass spectrometry data analysis, chemometrics, and machine learning to join our team. This position is part of our project Precision-MASH and fully-funded by Swiss National Science Foundation (SNSF).
What you can expect
The primary goal of this role is to advance the identification and screening of novel small molecules, with a particular focus on elucidating the structure and function of emerging lipids in metabolic disorders. The successful candidate will be responsible for developing computational pipelines for analyzing mass spectrometry dataset, integrating spectral data, building spectral library and applying chemometric and machine learning methods to enable in-silico annotation. Key Responsibilities: Develop and apply computational pipelines for identification and annotation of novel lipids. Perform in silico structural prediction of novel or low-abundance lipid species using advanced cheminformatics tools. Integrate multi-omics data with metabolic modeling approaches to investigate lipid flux and alterations in metabolic pathways. Design and implement chemometric and machine learning models for patient stratification based on spectral and imaging data.
Your Profile
Your Profile The ideal candidate should have a PhD or Master's with at least 5 years research experience in computational biology, system biology, bioinformatics, chemometrics. Proficiency in at least one programming language (R, MATLAB, Python) is essential. Prior track record in mass spectrometry spectral analysis or mass spectrometry imaging analysis, in silico chemical annotation and machine learning approaches is required. Knowledge of metabolism is a plus. We are looking for an enthusiastic individual with the ability to work both independently and collaboratively within the team. Good communication skills and fluency in both spoken and written English is essential.
What we offer
We provide the candidate with a supporting and state-of-the-art research environment to develop scientifically and professionally. The successful candidate will be able to work and get training on a multi-disciplinary research project. The candidate has the opportunity to work with large datasets generated from both pre-clinical and clinical studies. The position is available from Sep 2025 or upon agreement.
Questions about the job?
Questions about the job: For further information please contact: Prof. Mojgan Masoodi
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