Applied mathematics engineer – Autonomous driving

Job description
ADAGOS is the winner of the Grand Prize of the Continental Start-Up Challenge. It has developed a new parsimonious approach that reduces the resources (including energy) required for implementing artificial intelligence algorithms by orders of magnitude. This approach was the missing piece that will enable our partner Continental to complete the puzzle of embedding its artificial intelligence algorithms into the cars of the future; an ambition that requires hunting down and eliminating every possible source of wastage. For this aim, we are developing parsimonious convolutional dynamic neural networks.
We are seeking a talented R&D engineer with a background in applied mathematics. She or he should join our outstanding parsimonious convolutional neural networks team to contribute in developing efficient algorithms for autonomous driving.

Key responsibilities
● Contribute in designing, implementing and validating parsimonious neural networks algorithms
● Participate and collaborate with our European partners in the fields of autonomous driving
● Presentation (verbal and written) in English of findings, contributions to internal reports, invention disclosures and external publications and conference presentations.

Requirements
● Ideally a PhD in applied mathematics with a scientific computing background.
● Experience in inverse problems, data assimilation, control theory, optimization or algorithmic differentiation, would be appreciated, but there is no need to have particular skills in data science or statistics.
● Creativity, exceptional critical thinking and problem-solving skills that promote a goal-oriented work culture.
● Capable to adapt to face new challenges.
● Current authorization to work in France.

Type of contract: Permanent

City: Toulouse (France)

Please submit your resume and a cover letter detailing your interest and experience to contact@adagos.com. ADAGOS is offering a competitive salary and benefits package.