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AI Forest Genomics & Adaptation Research

Forestry
AI Forest Genomics & Adaptation Research
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AI Forest Genomics & Adaptation Research

Internship studying forest genomics with analysis of adaptation to climate and disease pressure. Hands-on work runs alongside theory modules.

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

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

Showing 1–5 of 5

Machine Learning for Forest Species Classification
Interns will develop and train deep learning models to classify tree species from genomic sequences and remote sensing imagery. They will work with large-scale forest datasets to improve species identification accuracy and create predictive models for biodiversity assessment.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £643
R · £935
3 Months
A · £846
T · £1,033
R · £1,503
6 Months
A · £1,878
T · £2,296
R · £3,339
14 more durationsView Titles →
Genomic Marker Development for Climate Adaptation
Interns will analyze genomic data from forest populations to identify genetic markers associated with drought, temperature, and pest resistance traits. This work involves SNP analysis, association studies, and developing tools to predict adaptive potential in tree species under climate change scenarios.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £643
R · £935
3 Months
A · £846
T · £1,033
R · £1,503
6 Months
A · £1,878
T · £2,296
R · £3,339
14 more durationsView Titles →
Bioinformatics Pipeline Development for Forest Genetic Analysis
Interns will design and implement automated bioinformatics workflows for processing whole-genome sequencing data from forest samples. They will work with tools like GATK, SAMtools, and custom Python scripts to handle quality control, variant calling, and annotation of forest tree genomes.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £643
R · £935
3 Months
A · £846
T · £1,033
R · £1,503
6 Months
A · £1,878
T · £2,296
R · £3,339
14 more durationsView Titles →
Population Genomics and Gene Flow Modeling
Interns will conduct population-level genomic analysis to understand genetic diversity, migration patterns, and gene flow within and between forest populations. They will use statistical models and visualization tools to assess population structure and inform conservation and reforestation strategies.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £643
R · £935
3 Months
A · £846
T · £1,033
R · £1,503
6 Months
A · £1,878
T · £2,296
R · £3,339
14 more durationsView Titles →
AI-Driven Phenotype Prediction from Genomic Data
Interns will apply machine learning algorithms to predict forest tree phenotypes (growth rate, wood quality, disease resistance) from genomic information. They will develop prediction models, validate results against field measurements, and create tools for early selection of superior tree genotypes.
Academic (A)Tech (T)Research (R)
1 Month
A · £268
T · £643
R · £935
3 Months
A · £846
T · £1,033
R · £1,503
6 Months
A · £1,878
T · £2,296
R · £3,339
14 more durationsView Titles →