Deep Learning Model Development for QTL Detection

Plant Breeding Genetics › Machine Learning QTL Mapping Research

Deep Learning Model Development for QTL Detection

Interns will develop and optimize convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to identify quantitative trait loci from genomic and phenotypic datasets. They will work with frameworks like TensorFlow and PyTorch to build models that outperform traditional statistical methods in detecting complex trait associations.

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