Postdoc: NAS & ML for Efficient Image Restoration

Tecnológico de Monterrey; México; Presencial; MXN 360.000 - 480.000; Jornada completa

Descripción de la vacante

Tecnológico de Monterrey invites applications for a Postdoctoral Researcher in Neural Architecture Search and Machine Learning. The position is full‑time for one year, with possible extension to a second year, starting September 2026, in the AI Research Group at the School of Engineering and Sciences, working with Prof.

Raúl Monroy. The project develops a multi‑objective NAS approach to automate DNN design, balancing accuracy with compute constraints.

Formación

• PhD in Computing or closely related field.
• Proven research track record in ML or multi‑objective optimisation.
• Experience in NAS, Deep Learning, Transfer Learning, or NLP.
• Strong publication record and drive to innovate and contribute in ML/NAS/NLP.
• Excellent organisational and communication skills in Spanish and English.
• Postdoctoral experience is an advantage.
• Teaching experience and supervision of student projects is a plus.

Responsabilidades

• Design and develop multi‑objective NAS methods to automate DNN design.
• Collaborate with a multidisciplinary team and supervise undergraduate and PhD student projects.
• Publish research findings in high‑impact journals and conferences.
• Validate NAS approaches on image restoration tasks balancing performance vs. compute resources.

Conocimientos

ML research

Multi‑objective optimisation

NAS

Deep Learning

Transfer Learning

NLP

Publications

Spanish‑English communication

Educación

PhD in Computing or related field

Descripción del empleo

Tecnológico de Monterrey invites applications for a Postdoctoral Researcher in Neural Architecture Search and Machine Learning. The position is full‑time for one year, with possible extension to a second year, starting September 2026, in the AI Research Group at the School of Engineering and Sciences, working with Prof.

Raúl Monroy. The project develops a multi‑objective NAS approach to automate DNN design, balancing accuracy with compute constraints.