ESR8: PhD fellowship in machine learning methods at the genome scale.
CDD · Thèse · 36 mois Bac+5 / Master University of Szeged (USZ) · Szeged (Hongrie)
Date de prise de poste : 1 septembre 2021
Machine learning on multi-omics data, feature selection, support mechanistic models with machine learning
A. Data-driven approach to examine biological systems. B. Identifying relevant features – feature extraction using neural networks. C. Use knowlegde from mechanistic models to develop biologically more meaningful data-driven models. D. Finding hidden patterns in omics data (https://www.itn-emuse.com/wp).
Master’s degree in computer science ideally with a strong background in data science, machine learning, deep learning.
- Computer science, data science, machine learning, deep learning background
- Provable software development skills in one of common programming languages (e.g. Java, C++)
- Python, Tensorflow, PyTorch experience is favoured
- Willingness to learn the necessary biology background in order to work with biological data properly
- You should NOT have any kind of PhD degree.
- Previous research experience (which must be no longer than 4 years) although appreciated, is not mandatory.
- Educational background and previous research experience relevant for the chosen position.
- Applicants must demonstrate fluent reading, writing and speaking abilities in English. English: B2, good oral and written communication skills in English are compulsory.
- Networking and communication skills in a multicultural and multidisciplinary environment Willingness to travel abroad for the purpose of research, training and dissemination
Procédure : Apply on E-MUSE website: https://www.itn-emuse.com/esr8
Date limite : 30 juin 2021
Offre publiée le 3 juin 2021, affichage jusqu'au 30 juin 2021