We are looking for a two years postdoctoral to investigate the genome annotations in non-model plants by means of machine learning approaches.

Genome annotations is one of the major bottlenecks to obtain high quality genomes, especially in non-model species. Efficient tools to evaluate the quality of a genome annotation are needed. The goal for this position is to develop a toolkit with several applications to evaluate genome annotations using K-mers and AI. This is a project developed in collaboration with Dr. Ian Morilla (UMA, Spain).

Qualifications
Applicants should have demonstrated experience in the field of bioinformatics and/or computational biology. They should be proficient in at least one programming language (preferably Python). The candidate should have proficiency on data science, with focus machine learning. Deep learning apsproaches will be a plus. Good English communication skills are essential. The applicants should have a PhD degree in the fields of Biology or Computational Science.

The applicant should meet the requirements needed to apply to CSIC work system (https://sede.csic.gob.es/servicios/formacion-y-empleo/bolsa-de-trabajo).

If you are interested in this position or have any questions, please contact Prof. Aureliano Bombarely or Prof. Ian Morilla
(abombarely@ibmcp.upv.es, ian.morilla@ihsm.uma-csic.es)