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PhD Student in Plant Science with Focus on Deep-Learning Conifer Genomics
2 months ago
As a PhD student in plant science, you will contribute to the development of deep-learning driven computational tools for efficient identification of transposable elements in large plant genomes. This project aims to advance our understanding of the complexities of transposable elements in plant genomes and their impact on genome evolution.
Key Responsibilities- Develop and apply deep-learning methods to identify transposable elements in plant genomes
- Construct a comprehensive TE dataset to capture the sequence diversity of TEs
- Predict TE insertion from genome sequences and analyze TE integration profiles
- Collaborate with experimentalists and computational scientists across various disciplines
- Master's degree in plant biology, machine-learning, bioinformatics, or a related field
- Experience in standard molecular biological techniques or machine-learning
- Proficiency in working with computers and programming languages such as R, Python, or Julia
- Very good written and oral English language skills
As a PhD student at Umeå University, you will have the opportunity to work in a dynamic and interdisciplinary research environment. You will be part of a team of researchers and students working on cutting-edge projects in plant science and machine-learning.
How to ApplyTo apply for this position, please submit your application, including your CV, cover letter, and contact information for at least two academic references. We look forward to receiving your application.
