Intern – Quantitative and Computational Modeling

20 hours ago


bangalore, India MetFlux Research Full time

Job Title: Intern—Quantitative & Computational ModelingLocation: Bengaluru-Rajarajeshwari Nagar / OnsiteOrganization: MetFlux Research Private LimitedEmployment Type: Internship (with potential conversion to full-time based on performance)About MetFlux ResearchMetFlux Research is building the ΩmeX ecosystem — a biology-first intelligence platform that integrates systems biology, multi-module analytics, and quantitative modeling to power precision health, personalization, and predictive R&D.Our modeling and analytics team supports:MetSights – practitioner-grade precision insights based on blood, gut, urine, and lifestyle dataMetSolve – in-silico, physiology-aware modeling for health and wellness innovationThis internship is designed for candidates who want to work at the intersection of biology, mathematics, data, and real-world health applications.Role OverviewAs an Intern – Quantitative & Computational Modeling, you will work closely with senior scientists and modelers to build, validate, and interpret data-driven and mechanistic models that support MetFlux’s ΩmeX ecosystem.You will gain hands-on exposure to:multi-modal health data integrationphysiological and pathophysiology-driven modelinganalytical and computational pipelines used in real production systemsThis role is ideal for fresh graduates who are analytically strong, curious about biological systems, and motivated to apply quantitative skills to meaningful health problems.What You Will Work OnYour work will directly contribute to:Data integration pipelines across blood, gut microbiome, urine metabolomics, and clinical dataMulti-modal physiological networks and pathway-level representationsData-driven, ML-assisted, and mechanistic models for different pathophysiological statesValidation of MetSights personalized insights using quantitative and biological checksKey ResponsibilitiesIntegrate and process multi-modal biological and clinical datasets for modeling workflows.Develop, simulate, and evaluate quantitative or computational models under guidance.Translate biological mechanisms and pathophysiology into mathematical or algorithmic representations.Validate models and pipelines both analytically (data/statistics) and biologically (mechanism plausibility).Document models, assumptions, datasets, and outputs in alignment with MetFlux standards.Support senior scientists in building physiology interpretation layers for the ΩmeX knowledge graph and MetSights modules.Who We’re Looking ForEducationCompleted MTech / MS (or final-year students) in:Computational BiologyBioinformaticsBiotechnology (with strong quantitative focus)Applied Mathematics / Engineering (with biology exposure)Core CompetenciesStrong understanding of computational and mathematical modeling concepts.Good working proficiency in MATLAB and Python.Ability to analyze, visualize, and interpret diverse data types.Sound statistical foundations for data analysis and inference.Ability to read and interpret scientific literature, especially mechanistic and clinical studies.Clear scientific writing and structured documentation skills.High attention to detail, reproducibility, and data quality.Nice to HaveAbility to break down complex modeling pipelines into smaller, interpretable modules.Exposure to machine learning in biological or health datasets.Familiarity with Git, notebooks, or basic automation workflows.Curiosity-driven mindset with evidence-based reasoning.Why Join UsCompetitive internship stipend.Hands-on experience in a real-world precision health and modeling program.Close mentorship from senior scientists working on systems biology and quantitative modeling.Learn how data, biology, and computation come together in applied health intelligence.Opportunity for full-time conversion based on performance and team fit.How to ApplySend your CV (and an optional short note on your interest) to: talent@metflux.in Subject Line: Intern – Quantitative & Computational Modelingalong with applying to this job post.



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