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Molecular Biology Internship Topics

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Molecular Biology Internships with Accommodation

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Showing 1–12 of 155 internship topics
Machine Learning Models for Transcription Factor Binding Prediction
Interns will develop and train neural network models to predict transcription factor binding sites across genomic sequences. They will work with publicly available ChIP-seq datasets, implement deep learning architectures, and validate predictions against experimental data to improve gene regulation prediction accuracy.
AI Gene Expression Regulation ResearchView internship →
CRISPR-Based Epigenetic Regulation and Gene Silencing Analysis
Interns will investigate how CRISPR-dCas9 systems can be used to modulate gene expression through epigenetic modifications. They will design experiments to analyze changes in histone marks and DNA methylation patterns, and use computational tools to assess the specificity and off-target effects of different guide RNA designs.
AI Gene Expression Regulation ResearchView internship →
Single-Cell RNA-seq Data Analysis for Cell-Type-Specific Gene Expression
Interns will process and analyze single-cell RNA sequencing datasets to identify cell-type-specific gene expression patterns and regulatory networks. They will apply clustering algorithms, differential expression analysis, and construct gene regulatory networks to understand developmental and tissue-specific expression dynamics.
AI Gene Expression Regulation ResearchView internship →
Non-Coding RNA Function in Post-Transcriptional Gene Regulation
Interns will study the regulatory roles of microRNAs, long non-coding RNAs, and circular RNAs in controlling gene expression at post-transcriptional levels. They will perform bioinformatics analysis of ncRNA-mRNA interactions, validate predictions using computational tools, and interpret functional outcomes in disease contexts.
AI Gene Expression Regulation ResearchView internship →
Synthetic Gene Circuits and Computational Modeling of Gene Networks
Interns will design and model synthetic gene regulatory circuits using computational biology tools and mathematical frameworks. They will develop models to predict system behavior, simulate dose-response relationships, and optimize circuit designs for specific outputs in biotechnology applications.
AI Gene Expression Regulation ResearchView internship →
RNA Structure Prediction Using Machine Learning
Interns will develop and train AI models to predict secondary and tertiary structures of RNA molecules from sequence data. They will work with datasets like RNAstralign and implement deep learning architectures such as graph neural networks and transformer models to improve prediction accuracy.
AI RNA Biology Molecular ResearchView internship →
CRISPR RNA Design and Optimization
Interns will use computational tools and AI algorithms to design optimal guide RNAs for CRISPR-Cas9 systems with improved specificity and efficiency. This includes analyzing off-target effects, predicting cleavage outcomes, and optimizing sgRNA sequences for various genomic targets.
AI RNA Biology Molecular ResearchView internship →
RNA-Protein Interaction Prediction
Interns will apply machine learning models to predict and analyze interactions between RNA molecules and proteins using sequence and structural data. They will validate computational predictions through literature mining and contribute to databases of RNA-binding protein targets.
AI RNA Biology Molecular ResearchView internship →
Single-Cell RNA Sequencing Data Analysis
Interns will process and analyze scRNA-seq datasets using bioinformatics pipelines and AI-based clustering algorithms to identify cell types and gene expression patterns. They will work with tools like Seurat and scanpy to uncover cellular heterogeneity and develop classification models.
AI RNA Biology Molecular ResearchView internship →
Non-coding RNA Functional Annotation
Interns will utilize deep learning and natural language processing techniques to predict functions of long non-coding RNAs (lncRNAs) and small regulatory RNAs. They will integrate multi-omics data to establish functional relationships and improve annotation databases.
AI RNA Biology Molecular ResearchView internship →
Deep Learning Models for Protein Structure Prediction
Interns will develop and train neural network architectures to predict 3D protein structures from amino acid sequences. They will work with datasets like CASP and implement attention mechanisms similar to AlphaFold, comparing model performance across different protein families and complexity levels.
AI Protein Synthesis ResearchView internship →
Machine Learning-Driven Codon Optimization
Interns will create algorithms to optimize DNA codon usage for improved protein expression in various organisms. They will analyze translation efficiency, GC content, and secondary structure predictions to maximize yields in recombinant protein production systems.
AI Protein Synthesis ResearchView internship →
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