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Genomics Internship Topics

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Genomics Internships with Accommodation

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Showing 1–12 of 15 internship topics
Variant Calling Pipeline Development
Interns will develop and optimize bioinformatics pipelines for identifying genetic variants from whole genome sequencing data. They will work with tools like GATK and SAMtools to process raw sequencing reads, call single nucleotide polymorphisms (SNPs), and indels, while implementing quality control measures and validating results against known variants.
AI Whole Genome Sequencing Analysis ResearchView internship →
Machine Learning for Pathogenic Variant Classification
Interns will build and train machine learning models to classify genetic variants as pathogenic, benign, or of uncertain significance. They will utilize deep learning frameworks and feature engineering techniques on genomic datasets to improve prediction accuracy for clinical variant interpretation.
AI Whole Genome Sequencing Analysis ResearchView internship →
Copy Number Variation Detection Using AI
Interns will develop AI algorithms to detect and characterize copy number variations (CNVs) in whole genome sequencing data. This work involves implementing neural networks and statistical methods to identify duplications and deletions, analyze their breakpoints, and assess their potential clinical significance.
AI Whole Genome Sequencing Analysis ResearchView internship →
Genome Assembly and Sequence Alignment Optimization
Interns will research advanced algorithms for genome assembly and sequence alignment, focusing on improving accuracy and computational efficiency. They will work with long-read sequencing technologies and implement or optimize tools for handling complex genomic regions and structural variants.
AI Whole Genome Sequencing Analysis ResearchView internship →
Population Genomics and Ancestry Analysis
Interns will analyze whole genome data across diverse populations to understand genetic variation patterns, population structure, and ancestry. They will apply principal component analysis, admixture modeling, and statistical methods to characterize genomic diversity and identify population-specific variants of interest.
AI Whole Genome Sequencing Analysis ResearchView internship →
Variant Annotation and Functional Prediction
Interns will develop and optimize machine learning pipelines to annotate genetic variants and predict their functional impacts on protein structure and disease susceptibility. Work includes training neural networks on existing variant databases and validating predictions against clinical phenotype data from population cohorts.
AI Population Genomics ResearchView internship →
Population Stratification and Ancestry Analysis
Interns will apply dimensionality reduction techniques and clustering algorithms to analyze genetic ancestry patterns across diverse populations using large-scale genomic datasets. Projects involve implementing PCA, UMAP, and admixture analysis tools to characterize population structure and identify ancestry-specific genetic effects.
AI Population Genomics ResearchView internship →
Genome-Wide Association Study (GWAS) Pipeline Development
Interns will design and implement automated GWAS pipelines using Python and R to identify genetic loci associated with complex traits and diseases at population scale. This includes quality control workflows, statistical association testing, and integration of results with biological databases for interpretation.
AI Population Genomics ResearchView internship →
Polygenic Risk Score Construction and Validation
Interns will develop computational methods to construct polygenic risk scores from GWAS summary statistics and validate their predictive accuracy across different populations and cohorts. Work involves exploring methods to reduce population bias and improve clinical utility of risk predictions.
AI Population Genomics ResearchView internship →
Single-Cell Population Genomics and Multi-omics Integration
Interns will apply machine learning techniques to integrate single-cell transcriptomic data with population-level genomic variation to understand cell-type-specific genetic effects. Projects include developing computational frameworks for linking genetic variants to cellular phenotypes using scRNA-seq and population genomics data.
AI Population Genomics ResearchView internship →
Whole Genome Sequencing (WGS) Pipeline Development
Interns will work on designing and optimizing bioinformatics pipelines for processing whole genome sequencing data, including quality control, alignment, and variant calling. They will learn to work with tools like BWA, GATK, and SAMtools while handling large-scale genomic datasets and implementing best practices for accuracy and efficiency.
Next-Generation Sequencing Data AnalysisView internship →
RNA-Seq Transcriptome Analysis and Gene Expression Profiling
Interns will analyze RNA sequencing data to quantify gene expression levels, perform differential expression analysis, and conduct pathway enrichment studies. They will gain hands-on experience with tools such as HISAT2, featureCounts, and DESeq2 to uncover biological insights from transcriptomic datasets.
Next-Generation Sequencing Data AnalysisView internship →
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