Missions

The NanoBio team develops novel fluorescence microscopy modalities that push the limits of observation, both in terms of acquisition speed and imaging depth, with applications ranging from biology to the study of nanomaterials.

These developments sit at the crossroads of multiple disciplines, involving expertise in optics, electronics, image and data processing, chemistry, and biology.
With the support of several European funding programs, the team is building a data science and machine learning group to drive innovation across the various microscopy-related fields.
The position is therefore particularly suited for candidates who wish to work at the heart of this interdisciplinarity, with training in one of these major domains and an interest in exploring the others.

Activities

The recruited candidate will contribute to various aspects of the project. Depending on their background and expertise, they will take a leading role in one of the activities.
Throughout the project, the main tasks will include:
-Assessing the theoretical performance of the system through modeling,
-Developing and training a self-supervised learning model,
-Evaluating model performance using both simulations and experimental data,
-Transitioning from a task-specific model to a foundation model,
-Benchmarking results against state-of-the-art techniques,
-Preparing progress reports and/or scientific publications,
-Presenting results at national and international conferences.

Skills

Technical skills are expected in machine learning, applied mathematics, or image processing, combined with advanced programming proficiency in Python.
The ideal candidate will have previous experience in machine learning, particularly in self-supervised learning. They should have knowledge of, or experience with, unlabeled data problems, pretext tasks, and approaches related to pre-training, transfer learning, and fine-tuning.
Beyond technical expertise, the candidate is expected to show a strong interest in the scientific implications of machine learning. They should be able to communicate regularly about their work and demonstrate a genuine enthusiasm for teamwork and interdisciplinarity.

Work Context

This work will take place at ISMO (a joint CNRS / Université Paris-Saclay research unit) as part of the ERC project TimeNanoLive, within the interdisciplinary NanoBio team.
The laboratory is equipped with an on-site cell culture facility and several single-molecule localization microscopes.
The contract duration can be extended.

Constraints and risks

laser beam
culture cell