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

Mots-Clés

Machine learning on multi-omics data, feature selection, support mechanistic models with machine learning

Description

ESR8 Objectives

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).

Skills/Qualifications

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

Specific Requirements

  • 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


Candidature

Procédure : Apply on E-MUSE website: https://www.itn-emuse.com/esr8

Date limite : 30 juin 2021

 https://www.itn-emuse.com/esr8

Offre publiée le 3 juin 2021, affichage jusqu'au 30 juin 2021