Name: Bright Enogieru Osatohanmwen
E-Mail: bright.osatohanmwen“€“uni-goettingen.de
Start of Ph.D. project and thesis: December 2022
Presumed end of Ph.D. project and thesis: December 2025
Working title of Ph.D. thesis: "Modelling non-addictive effects in genomic prediction using classical and machine learning methods."
The Ph.D. project aims to improve the genomic prediction accuracy by combining modeling of additive, dominance, and epistasis effects using Genomic Best Linear Unbiased Prediction (GBLUP), Gradient-Boosted Decision Trees (GBDT), and Convolutional Neural Networks (CNN).

The Ph.D. project was supervised until February 2023 by Tim Beissinger.
Current Ph.D. thesis committee: Reza Sharifi (https://www.uni-goettingen.de/de/104191.html); Tim Beissinger (https://orcid.org/0000-0002-2882-4074); Reimund Rötter (https://www.uni-goettingen.de/de/536039.html); Indalécio Cunha Vieira Júnior (www.researchgate.net/profile/Indalecio-Vieira-Junior).

Financial basis of the Ph.D. project: KWS SAAT SE and Plant Breeding Methodology Group of the University of Göttingen.
Budget of the PhD project was acquired by Tim Beissinger.