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NGS Internship Topics

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

NGS Internships with Accommodation

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Showing 1–12 of 20 internship topics
Machine Learning Model Optimization for Variant Calling
Interns will research and implement deep learning models to improve accuracy in NGS variant calling pipelines. Work involves experimenting with neural network architectures, training on benchmark datasets, and comparing performance against existing tools like GATK and SAMtools.
AI NGS Data Pipeline ResearchView internship →
Quality Control and Data Filtering Algorithms
Develop and validate automated QC algorithms for NGS raw sequencing data, including read quality assessment, contamination detection, and filtering strategies. Interns will implement statistical methods to identify and handle problematic samples in large-scale datasets.
AI NGS Data Pipeline ResearchView internship →
Sequence Alignment Pipeline Acceleration
Optimize NGS read alignment workflows through algorithm research and parallel processing implementation. Interns will benchmark existing aligners, implement hardware acceleration techniques, and develop novel indexing strategies to reduce computational bottlenecks.
AI NGS Data Pipeline ResearchView internship →
Annotation and Functional Impact Prediction
Research and integrate bioinformatics tools for variant annotation and functional impact assessment in NGS pipelines. Interns will work on predicting pathogenicity, cross-referencing genomic databases, and implementing machine learning models for clinical significance scoring.
AI NGS Data Pipeline ResearchView internship →
Scalable Data Management and Pipeline Architecture
Design and implement scalable data structures and workflow management systems for NGS processing at scale. Interns will explore containerization, cloud computing integration, and database optimization techniques for handling multi-terabyte genomic datasets efficiently.
AI NGS Data Pipeline ResearchView internship →
De Novo Transcriptome Assembly Pipeline Optimization
Interns will evaluate and optimize de novo assembly algorithms (Trinity, SPAdes, IDBA-UD) for RNA-Seq data, focusing on parameter tuning and computational efficiency. They will benchmark different assembly strategies against reference genomes and develop workflows for non-model organisms with limited genomic resources.
RNA-Seq Transcriptome Assembly OptimizationView internship →
Quality Assessment and Error Correction in RNA-Seq Assemblies
Interns will implement quality control metrics (BUSCO, TransRate, DETONATE) to evaluate transcriptome completeness and accuracy. They will develop and test error correction methodologies to improve assembly quality and reduce false transcript predictions from sequencing artifacts.
RNA-Seq Transcriptome Assembly OptimizationView internship →
Transcript Isoform Detection and Characterization
Interns will work on identifying and quantifying alternative splicing variants and isoforms from assembled transcriptomes using tools like StringTie and IsoQuant. They will analyze isoform-level expression patterns and their functional implications in different biological conditions.
RNA-Seq Transcriptome Assembly OptimizationView internship →
Comparative Transcriptomics Assembly Framework Development
Interns will design computational frameworks for comparative analysis of transcriptome assemblies across multiple samples or species. They will develop pipelines for orthologue identification, differential transcript expression analysis, and cross-species transcriptome integration.
RNA-Seq Transcriptome Assembly OptimizationView internship →
Long-Read and Short-Read Hybrid Assembly Integration
Interns will explore hybrid assembly strategies combining PacBio/Nanopore long reads with Illumina short reads for improved transcript structure resolution. They will optimize computational workflows for hybrid approaches and evaluate their effectiveness in resolving complex isoforms and full-length transcripts.
RNA-Seq Transcriptome Assembly OptimizationView internship →
Real-time Phylogenetic Analysis of Viral Outbreaks
Interns will learn to construct and interpret phylogenetic trees from viral genomic sequences to track outbreak transmission patterns and identify zoonotic spillover events. They will work with bioinformatics tools like BEAST and IQ-TREE to analyze temporal and spatial distribution of viral variants during active outbreaks.
Viral Genome Sequencing Outbreak InvestigationView internship →
Viral Variant Identification and Classification
Interns will learn to identify and classify viral variants from NGS data using bioinformatics tools and reference databases. They will analyze sequence alignments, detect single nucleotide polymorphisms (SNPs), and insertions/deletions to determine variant lineages and assess their epidemiological significance in outbreak scenarios.
Viral Genome Sequencing Outbreak InvestigationView internship →
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