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Cancer Microbiology Internship Topics

Browse all focused areas across all internship categories under this field.

Cancer Microbiology Internships with Accommodation

Choose an internship topic, then explore accommodation-enabled internship options at active NTHRYS branch locations in India.

Showing 1–12 of 15 internship topics
Microbial DNA Sequence Analysis and Taxonomic Classification
Interns will process raw sequencing data from tumor samples using bioinformatic pipelines to identify and classify microbial species present in the tumor microbiome. They will work with tools like QIIME2 and 16S rRNA gene analysis to generate taxonomic profiles and evaluate microbial diversity metrics across different cancer types.
AI Tumor Microbiome Characterization ResearchView internship →
Machine Learning Model Development for Microbiome Prediction
Interns will develop and train AI/ML models to predict tumor-associated microbial signatures and their correlation with cancer progression, treatment response, and patient outcomes. This includes feature selection, model validation, and performance optimization using Python and scikit-learn frameworks.
AI Tumor Microbiome Characterization ResearchView internship →
Functional Metabolic Pathway Analysis of Tumor Microbes
Interns will analyze metagenomic and metatranscriptomic data to identify metabolic functions and pathways produced by tumor-associated microorganisms. They will use computational tools to link microbial activities to immune modulation and cancer phenotypes.
AI Tumor Microbiome Characterization ResearchView internship →
Integration of Multi-Omics Data for Microbiome-Cancer Phenotyping
Interns will integrate microbiome data with genomic, proteomic, and immunological datasets to create comprehensive profiles of tumor-microbiome interactions. They will develop analytical workflows to correlate microbial composition with host immune responses and tumor characteristics.
AI Tumor Microbiome Characterization ResearchView internship →
Deep Learning Model Optimization for Medical Image-Microbiome Correlation
Interns will apply deep learning techniques to correlate tumor imaging features with microbiome composition data, developing neural network architectures to predict microbiome profiles from imaging biomarkers. This includes model architecture design, hyperparameter tuning, and cross-validation studies.
AI Tumor Microbiome Characterization ResearchView internship →
HPV Genome Sequencing and Variant Classification
Interns will analyze whole-genome and targeted sequencing data from HPV-infected samples to identify viral variants, mutations, and their oncogenic potential. They will use bioinformatics tools to classify HPV strains and correlate genomic signatures with cancer risk profiles, contributing to understanding viral evolution in malignant progression.
AI HPV & Viral Oncogenesis ResearchView internship →
Machine Learning Models for HPV-Cancer Progression Prediction
Interns will develop and train AI/ML algorithms using clinical datasets to predict cancer development risk based on HPV viral load, integration patterns, and host genetic factors. This work involves feature engineering, model validation, and creating interpretable predictive tools for clinical decision support.
AI HPV & Viral Oncogenesis ResearchView internship →
Viral Integration Mapping and Oncogenic Driver Identification
Interns will analyze HPV integration sites in host genomic DNA using computational methods to identify disrupted genes and oncogenic hotspots associated with malignant transformation. They will map integration patterns across cancer samples and correlate findings with transcriptomic changes driving viral oncogenesis.
AI HPV & Viral Oncogenesis ResearchView internship →
Immunoinformatics and HPV-Antigen Prediction Analysis
Interns will use computational approaches to predict immunogenic epitopes from HPV proteins (E6, E7) and assess immune escape mechanisms in oncogenic strains. This includes analyzing MHC-peptide binding, T-cell receptor interactions, and developing data for immunotherapy target identification.
AI HPV & Viral Oncogenesis ResearchView internship →
Multi-Omics Integration in Viral Oncogenesis Studies
Interns will integrate genomics, transcriptomics, and proteomics data from HPV-infected tissues to construct comprehensive mechanistic models of viral-induced malignant transformation. They will perform pathway analysis and identify molecular biomarkers that distinguish between productive infection and cancer-driving viral persistence.
AI HPV & Viral Oncogenesis ResearchView internship →
Bacterial Microbiota Profiling in Glioblastoma Tissues
Interns will learn 16S rRNA gene sequencing and metagenomic analysis techniques to identify and characterize bacterial communities within glioblastoma tumor samples. They will analyze microbial diversity patterns, compare community structures between tumor and adjacent normal brain tissue, and compile comprehensive taxonomic profiles using bioinformatics tools.
Microbial Biomarker Discovery Glioblastoma PatientsView internship →
Identification of Pathogenic Microbial Species as Diagnostic Biomarkers
Interns will conduct targeted isolation and identification of specific bacterial and fungal species from glioblastoma patient samples using culture-dependent and molecular methods. They will validate candidate microbial biomarkers through quantitative PCR and develop diagnostic panels that correlate microbial presence with tumor progression and patient outcomes.
Microbial Biomarker Discovery Glioblastoma PatientsView internship →
Want to browse internship categories in Cancer Microbiology? Explore all Cancer Microbiology internship categories.