Post-Doctoral Research Visit F/M Postdoc in parallel numerical optimization and statistical machine learning

1000scholars; Grenoble; Sur place; EUR 36 000 - 48 000; Plein temps

Avantages offerts par ce poste

None

Résumé du poste

1000scholars in Grenoble invites applications for a research-focused role to implement and benchmark parallel and stochastic numerical optimization algorithms within the Thoth project at the Inria Centre. You will contribute to software development for PEPit, read and analyze scientific reports, and prepare formal reports for dissemination.

The position requires a Master’s level degree in CS, math, or engineering, plus excellent English and strong teamwork.

Qualifications

• Master's level degree in computer science, mathematics, applied mathematics, or engineering.
• English language required for collaboration and reporting.
• Strong communication, sociable with teamwork ability.

Responsabilités

• Implement and benchmark parallel and stochastic numerical optimization algorithms.
• Participate in the development and maintenance of the PEPit software package.
• Read scientific reports and write scientific reports.

Connaissances

Mastering teamwork

Autonomy

English proficiency

Optimization focus

Curiosity

Proactiveness

Formation

Master's degree in CS/Math/Engineering

Description du poste

Context The successful candidate will join the Thoth project team (https://thoth.inrialpes.fr/) within the Inria Centre at Université Grenoble Alpes (https://www.inria.fr/en/inria-center-universite-grenoble-alpes) to work under the supervision of Adrien Taylor and Scott Pesme.

Assignment

• The successful candidate will implement and compare different parallel and stochastic numerical optimization paradigms
• accurately study the selected algorithms
• participate in the development and maintenance of the PEPit (https://pepit.readthedocs.io/) software package, including adding functionalities related to parallel optimization

Main activities

• Implementation and benchmark of numerical optimization algorithms.
• Software maintenance and development.
• Read scientific reports.
• Write scientific reports.

Skills

• Technical skills and level required: master's level in computer science, mathematics, applied mathematics, or engineering.
• Languages: English.
• Relational skills: easy communication, sociable with an appetite for working in a group.
• Additional skills appreciated: rigorous, organized, curious, autonomous, proactive and dynamic.
• A specialization in optimization, machine learning, statistical learning or game theory is appreciated.
• Research experience is a plus.