Internship in Deep Learning – Analysis of Biological Data

Contract type : Internship agreement

Level of qualifications required : Master's or equivalent

Other valued qualifications : Certificate(s) in deep learning or in data analysis

Fonction : Internship Engineering

Level of experience : Up to 3 years

Context

About LabSae

LabSae is a start-up backed by INRIA offering a unified computational platform for analyzing protein-protein interaction networks using computational biology and artificial intelligence. Proteins orchestrate a wide range of biological processes in living organisms, making them prime targets for many pharmaceutical interventions. LabSae provides a reliable and accurate large-scale computational analysis of protein-protein interactions that significantly improves our knowledge of proteins and therefore facilitates preclinical in-silico drug design.

Assignment

We look forward to welcoming talented individuals who are passionate about leveraging new advances in deep learning and computational biology to develop algorithms for analyzing protein structures and sequences.

Main activities

Develop/utilize deep learning models for applications in computational biology, with a focus on addressing challenges related to proteins and their interactions.

Utilize data science techniques to analyze and interpret protein structures and sequences.

Collaborate with an innovative and interdisciplinary team in a dynamic environment.

Contribute to innovation through proactive problem-solving and research.

 

Skills

The ideal profile for us

  • Experience in deep learning and its packages such as TensorFlow, PyTorch, or Keras, along with good knowledge of data science methodologies.
  • Expertise in programming languages, particularly Python.
  • Experience working in collaborative development.
  • Good knowledge of computational biology.
  • Good level of English.

 

Soft skills

  • Autonomy
  • Effective communication skills
  • Teamwork abilities and collaborative mindset

Benefits package

  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
  • Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
  • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage