Masmicrobiota
Scientic Supervisor / Contact Person
Name and Surname
MAR LARROSA
ORCID (link)
Localization & Research Area
Faculty / Institute
Faculty of Pharmacy
Department
Nutrition and Food Science
Research Area
Life Sciences (LIF)
MSCA & ERC experience
Research group / research team hosted any MSCA fellow?
No
Research group / research team have any ERC beneficiaries?
No
Research Team & Research Topic
Research Team / Research Group Name (if any)
Masmicrobiota (Microbiota, Alimentación y Salud- Microbiota, Food and Health)
Website of the Research team / Research Group / Department
Brief description of the Research Team / Research Group / Department
The MASmicrobiota research group, led by Mar Larrosa, is a multidisciplinary team dedicated to studying how lifestyle factors, particularly diet and physical activity, impact gut microbiota and health. The team integrates expertise in nutrition, microbiology, genetics, data science, and sports sciences, employing advanced metagenomics, bioinformatics, and AI-based predictive analytics. PhD. Mar Larrosa specializes in the effects of diet and exercise on inflammation, oxidative stress, and microbiota. PhD. Rocío González Soltero focuses on genetics, while PhD. Carlo Bressa applies big data techniques and metagenomic analysis to microbiota research. PhD María Bailén Andrino studies antimicrobial compounds, PhD. Beatriz González Gálvez, an expert in stem cell research contributes insights into the cellular mechanisms influenced by microbiota. PhD. Sara Martínez investigates the bioavailability and health effects of bioactive ingredients. PhD. Mariangela Tabone explores microbiota-metabolome interactions, while Beatriz de Lucas Moreno examines the role of nutrition in gastrointestinal health and PhD. Diego Domínguez Balmaseda analyzes the relationship between sports performance and microbiota. Sara Clemente Velasco is a predoctoral researcher that works on the TREAT project, using AI to design personalized microbiota-based supplements for Alzheimer’s patients. Together, they advance the understanding of microbiota’s role in health and disease, aiming to develop personalized interventions through a combination of experimental and computational approaches.
Research lines / projects proposed
Our research group focuses on investigating how lifestyle factors, particularly diet and physical activity, influence gut microbiota and overall health. Our main objective is to understand the complex interactions between these lifestyle components and the microbial ecosystem in both healthy individuals and those with various diseases. To achieve this, we employ advanced metagenomic and bioinformatics techniques to analyze microbial composition and function. Additionally, we integrate predictive analytics powered by artificial intelligence (AI) to identify patterns and biomarkers associated with health and disease. Our multidisciplinary approach allows us to explore the potential of microbiota modulation as a strategy for disease prevention and personalized interventions.
Key words
Application requirements
Professional Experience & Documents
Postdoctoral Researcher Position – MASmicrobiota Group
We are looking for a motivated postdoctoral researcher to join the MASmicrobiota group, with a focus on bioinformatics and microbiome research. The ideal candidate should have experience in analyzing microbiota data and applying computational tools to study the impact of lifestyle factors (diet and exercise) on gut health.
Required Qualifications & Experience:
Ph.D. in Bioinformatics, Computational Biology, Microbiology, Biostatistics, or a related field.
• Basic experience in metagenomic data analysis and microbiota research.
• Knowledge of bioinformatics tools for microbiota analysis (QIIME2, MetaPhlAn, or similar).
• Experience with data analysis using R or Python (basic scripting, data visualization, and statistical analysis).
• Familiarity with microbial ecology and gut microbiota research.
• Interest in machine learning and predictive models, even at an introductory level.
• Ability to work with large biological datasets and interpret results in the context of human health.
• Good publication record and ability to work in a multidisciplinary research team.
Preferred Experience (Not Mandatory):
Some knowledge of multi-omics data integration (metagenomics, metabolomics, transcriptomics).
Basic understanding of clinical and nutritional research related to microbiota.
Familiarity with network analysis or AI-based prediction models.
The selected candidate will work in a collaborative research environment, alongside nutritionists, microbiologists, geneticists, and sports scientists, to explore the relationship between lifestyle, gut microbiota, and health. The role offers the opportunity to develop computational and analytical skills in microbiome research while contributing to personalized nutrition strategies.
How to Apply:
Interested candidates should send their CV, a brief motivation letter, and contact details of at least one reference to mlarrosa@ucm.es
We are looking for a motivated postdoctoral researcher to join the MASmicrobiota group, with a focus on bioinformatics and microbiome research. The ideal candidate should have experience in analyzing microbiota data and applying computational tools to study the impact of lifestyle factors (diet and exercise) on gut health.
Required Qualifications & Experience:
Ph.D. in Bioinformatics, Computational Biology, Microbiology, Biostatistics, or a related field.
• Basic experience in metagenomic data analysis and microbiota research.
• Knowledge of bioinformatics tools for microbiota analysis (QIIME2, MetaPhlAn, or similar).
• Experience with data analysis using R or Python (basic scripting, data visualization, and statistical analysis).
• Familiarity with microbial ecology and gut microbiota research.
• Interest in machine learning and predictive models, even at an introductory level.
• Ability to work with large biological datasets and interpret results in the context of human health.
• Good publication record and ability to work in a multidisciplinary research team.
Preferred Experience (Not Mandatory):
Some knowledge of multi-omics data integration (metagenomics, metabolomics, transcriptomics).
Basic understanding of clinical and nutritional research related to microbiota.
Familiarity with network analysis or AI-based prediction models.
The selected candidate will work in a collaborative research environment, alongside nutritionists, microbiologists, geneticists, and sports scientists, to explore the relationship between lifestyle, gut microbiota, and health. The role offers the opportunity to develop computational and analytical skills in microbiome research while contributing to personalized nutrition strategies.
How to Apply:
Interested candidates should send their CV, a brief motivation letter, and contact details of at least one reference to mlarrosa@ucm.es
One Page Proposal
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