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NTHRYSInternshipsAi Cancer Biology

AI Pan-Cancer Multi-Omics Integration Research

Ai Cancer Biology
AI Pan-Cancer Multi-Omics Integration Research
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AI Pan-Cancer Multi-Omics Integration Research

Internship integrating multi-omics layers across cancer types with AI to find shared vulnerabilities and subtype logic. Includes mentored hands-on analysis sessions.

The focused areas below are internship topics in varied working formats. Pick one, then choose your internship type, mode… Read more

🎓 TYPE
🌐 MODE
📚 Academic: Thesis & PPT assistance included🧪 Tech: Master the protocols hands-on📝 Research > 3 months: Publication co-authorship in a Scopus-indexed journal
🔍

Showing 110 of 10

Cross-Cancer Transcriptomic Pathway Convergence Analysis
This research investigates how distinct cancer types converge on shared transcriptomic pathways despite originating from different tissues and genetic backgrounds. The study reveals fundamental biological principles of cancer evolution and identifies universal therapeutic targets applicable across multiple malignancies.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £747
R · £1,086
3 Months
A · £982
T · £1,200
R · £1,746
6 Months
A · £2,182
T · £2,667
R · £3,879
14 more durationsView Titles →
Integrative Genomic Mutational Signature Profiling Across Tumor Types
This research examines mutational signatures across pan-cancer datasets to decode etiology, mechanisms, and environmental exposures underlying diverse malignancies. The analysis produces a comprehensive mutational taxonomy that enables cancer subtype classification and predicts treatment response with precision.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £812
R · £1,181
3 Months
A · £1,067
T · £1,304
R · £1,897
6 Months
A · £2,371
T · £2,898
R · £4,215
14 more durationsView Titles →
Multi-Omics Immune Microenvironment Stratification in Solid Tumors
This research integrates genomic, transcriptomic, proteomic, and spatial omics data to characterize immune cell populations and their functional states across heterogeneous tumor microenvironments. The integration reveals critical immune signatures that predict immunotherapy responsiveness and guide rational treatment selection.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £830
R · £1,207
3 Months
A · £1,092
T · £1,334
R · £1,940
6 Months
A · £2,425
T · £2,964
R · £4,311
14 more durationsView Titles →
Temporal Epigenetic Dynamics and Chromatin Remodeling Pan-Cancer Evolution
This research investigates how epigenetic modifications and chromatin landscape changes drive clonal evolution and drug resistance across multiple cancer lineages. The temporal analysis elucidates reversible epigenetic mechanisms that offer novel intervention points for preventing treatment escape.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £750
R · £1,091
3 Months
A · £986
T · £1,205
R · £1,753
6 Months
A · £2,191
T · £2,678
R · £3,895
14 more durationsView Titles →
Metabolomic-Genomic Networks Linking Tumor Metabolic Phenotypes
This research constructs integrative networks connecting metabolic pathway alterations with underlying genetic and epigenetic changes across pan-cancer cohorts. The analysis identifies metabolic vulnerabilities and reveals how different cancers exploit common metabolic dependencies for survival.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £799
R · £1,163
3 Months
A · £1,051
T · £1,285
R · £1,868
6 Months
A · £2,335
T · £2,854
R · £4,151
14 more durationsView Titles →
Spatial Proteogenomics Mapping Tumor Architecture and Cell Ecosystems
This research combines spatial transcriptomics, proteomics, and genomics to map three-dimensional tumor ecosystems and define interactions between malignant and stromal compartments. The integrative approach reveals context-dependent gene expression patterns and cell-cell communication networks essential for tumor survival.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £775
R · £1,127
3 Months
A · £1,019
T · £1,245
R · £1,811
6 Months
A · £2,263
T · £2,766
R · £4,023
14 more durationsView Titles →
Machine Learning Classification of Cancer Subtypes Using Integrated Omics
This research develops and validates sophisticated machine learning algorithms that integrate multiple omics modalities to discover and classify novel cancer subtypes with distinct biology and prognosis. The computational framework generates robust molecular classifiers that advance precision oncology and treatment stratification.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £833
R · £1,212
3 Months
A · £1,096
T · £1,339
R · £1,948
6 Months
A · £2,434
T · £2,975
R · £4,327
14 more durationsView Titles →
Circulating Biomarker Discovery Through Liquid Biopsy Multi-Omics Integration
This research mines multi-omics datasets from circulating tumor DNA, RNA, proteins, and exosomes to identify minimally invasive biomarkers for cancer detection, monitoring, and treatment response. The integrated approach establishes clinically actionable liquid biopsy signatures for early diagnosis and real-time disease tracking.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £799
R · £1,163
3 Months
A · £1,051
T · £1,285
R · £1,868
6 Months
A · £2,335
T · £2,854
R · £4,151
14 more durationsView Titles →
Network Pharmacogenomics Predicting Drug Sensitivity and Resistance Mechanisms
This research integrates pharmacogenomic data with multi-omics networks to predict cellular drug responses and mechanistically explain treatment resistance across diverse cancer types. The computational approach identifies therapeutic combinations and biomarkers that overcome acquired resistance.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £735
R · £1,068
3 Months
A · £966
T · £1,180
R · £1,717
6 Months
A · £2,146
T · £2,623
R · £3,814
14 more durationsView Titles →
Germline-Somatic Integration Identifying Cancer Predisposition and Driver Interactions
This research systematically integrates germline genetic variation with somatic mutations and omics alterations to dissect how inherited susceptibility shapes tumor evolution and therapeutic vulnerability. The analysis identifies synergistic germline-somatic interactions that explain variable cancer penetrance and prognosis.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £803
R · £1,167
3 Months
A · £1,055
T · £1,290
R · £1,875
6 Months
A · £2,344
T · £2,865
R · £4,167
14 more durationsView Titles →