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Genetics Internship Topics

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Genetics 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
Genomic Prediction Model Development
Interns will develop and validate machine learning models for predicting phenotypic traits from genomic data using algorithms such as ridge regression, LASSO, and random forests. They will work with real datasets to optimize model performance, evaluate cross-validation strategies, and compare traditional quantitative genetics approaches with modern ML techniques.
Machine Learning Quantitative Genetics ResearchView internship →
Variant Effect Prediction and Classification
Interns will implement deep learning models to classify and predict the functional impact of genetic variants on protein function and disease susceptibility. They will utilize existing databases like ClinVar and gnomAD, develop ensemble classification approaches, and validate predictions against experimental data.
Machine Learning Quantitative Genetics ResearchView internship →
Heritability and Gene-Environment Interaction Analysis
Interns will apply machine learning methods to estimate heritability components and detect gene-environment interactions from large-scale genomic and phenotypic datasets. They will implement algorithms like variance partitioning, interaction networks, and causal inference models to identify complex genetic architectures.
Machine Learning Quantitative Genetics ResearchView internship →
Population Stratification and Admixture Analysis
Interns will develop clustering and dimensionality reduction pipelines using techniques such as PCA, t-SNE, and neural networks to characterize population genetic structure and admixture patterns. They will process whole-genome sequencing data and validate population assignments against demographic metadata.
Machine Learning Quantitative Genetics ResearchView internship →
Quantitative Trait Loci (QTL) Mapping with ML Integration
Interns will implement machine learning approaches for detecting significant QTLs and genomic regions associated with quantitative traits in mapping populations. They will compare traditional statistical methods with neural networks and gradient boosting approaches, and develop visualization tools for complex genomic associations.
Machine Learning Quantitative Genetics ResearchView internship →
CRISPR Off-Target Effects Analysis
Interns will investigate and characterize unintended genetic modifications caused by CRISPR-Cas9 systems using computational prediction tools and experimental validation methods. They will analyze sequencing data to identify off-target sites and develop strategies to minimize off-target activity in therapeutic applications.
CRISPR Gene Editing Therapeutic DevelopmentView internship →
Gene Delivery Vector Optimization
Interns will work on optimizing viral and non-viral delivery systems for CRISPR components to target tissues with improved efficiency and reduced immunogenicity. This includes evaluating AAV serotypes, lipid nanoparticles, and electroporation techniques for various cell types and disease models.
CRISPR Gene Editing Therapeutic DevelopmentView internship →
CRISPR Base Editing and Prime Editing Development
Interns will explore advanced CRISPR variants including base editors and prime editors that enable precise nucleotide changes without double-strand breaks. They will test these systems on disease-causing mutations and assess their efficiency and accuracy compared to conventional CRISPR-Cas9.
CRISPR Gene Editing Therapeutic DevelopmentView internship →
Disease Model Development for CRISPR Therapeutics
Interns will create or utilize cellular and animal disease models to test CRISPR-based therapeutic interventions for genetic disorders. They will conduct phenotypic analysis, functional assays, and measure therapeutic efficacy in correcting disease-related mutations.
CRISPR Gene Editing Therapeutic DevelopmentView internship →
CRISPR Immunogenicity and Safety Assessment
Interns will evaluate immune responses triggered by CRISPR components and delivery vehicles in in vitro and in vivo systems. They will analyze innate immune activation, off-target immune effects, and develop strategies to improve safety profiles for clinical translation.
CRISPR Gene Editing Therapeutic DevelopmentView internship →
Off-Target Effects Assessment in CRISPR-Cas9 Systems
Interns will investigate and characterize unintended genomic modifications resulting from CRISPR-Cas9 editing. Research will involve whole-genome sequencing analysis, bioinformatics tools for off-target prediction, and experimental validation of potential off-target sites to improve editing precision and safety.
CRISPR Gene Editing Applications ResearchView internship →
Base Editing and Prime Editing Optimization
Interns will work on developing and optimizing advanced CRISPR variants including cytosine base editors (CBEs) and prime editors (PEs) for specific genetic modifications. This involves designing sgRNA libraries, testing editing efficiency across different cell types, and evaluating precision improvements over traditional CRISPR-Cas9.
CRISPR Gene Editing Applications ResearchView internship →
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