Postdoc / FTC researcher (M/F) in computer sciences / Mathematics, 34 months

Job title:

Postdoc / FTC researcher (M/F) in computer sciences / Mathematics, 34 months

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Job description

Offer DescriptionThe Roboscope project proposes a fast and generic automated microscope using only a few training images (Bonnet et al. (2024) bioRxiv, doi: 10.1101/2024.09.24.614735). Autonomous microscopes of this kind will be the basic tools for tomorrow’s life sciences research. The Roboscope makes it possible to study rare or brief processes without indiscriminate streams of unqualified images to be sorted afterwards; it also avoids long experiments and hence, damage to the sample. We have produced an initial prototype. However, in order to be usable in a wide range of environments and thus deploy this technology in imaging facilities, we have identified three essential developments:
(1) Enable the use of custom-specific algorithms from recent publications, whether for image segmentation to localise objects of interest, to refine or finalise the classification or to guide photo-manipulation of the sample. (2) Basing decisions on temporal series of images, integrating domain knowledge on the succession of events (the classes in our deep network). (3) To further facilitate training, in particular by using semi-synthetic images and allowing a human-in-the-loop approach to focus the experimenter’s effort on objects that are difficult to localise or classify.
Naturally, the application of the roboscope to the detection of transient processes requires rapid operation via embedded algorithms. Along that line, we are also working on speeding up the image pre-processing stages using a dedicated camera. This work is being valorised by the start-up Inscoper, which was created in 2016 and with which we have a long-term scientific collaboration.The successful candidate will (i) determine and implement the algorithms and methods to achieve the above objectives in order to create a prototype. He/she will work in close collaboration with Inscoper’s engineers, in particular on the embedding aspects. (ii) Secondly, the researcher will support the development of a few biology applications demonstrating the prototype’s capabilities, teaming up with the biology engineers and technicians recruited for the project. (iii) Finally, the researcher will support the transfer to Inscoper to envisage industrialisation. Particular attention will be paid to the user experience. The company will develop the appropriate interfaces in conjunction with the candidate recruited.

Work on the project will be carried out within the CeDRE team led by Jacques Pécréaux, in close collaboration with Marc Tramier’s team at the Institut de Génétique et Développement de Rennes (IGDR). The project will also be conducted in collaboration with Inscoper’s R&D teams. The IGDR is a fundamental research institute under the supervision of the CNRS, the University of Rennes and INSERM. Its research covers a wide range of disciplines, including cell and developmental biology, biophysics, genetics and genomics, bioinformatics and advanced microscopy. The CeDRE ‘Reverse Engineering of Cell Division’ team is interdisciplinary, with specialists in biology, physics, image processing and artificial intelligence studying cell division using a cellular biophysics approach. We aim to understand the robustness of cell division by measuring and modelling the biophysical and mechanical interactions between the molecular players. We set out to validate our results in human cells using the roboscope.Where to apply WebsiteRequirementsResearch Field Biological sciences Education Level PhD or equivalentResearch Field Computer science Education Level PhD or equivalentResearch Field Mathematics Education Level PhD or equivalentLanguages FRENCH Level BasicResearch Field Biological sciences Years of Research Experience 1 – 4Research Field Computer science Years of Research Experience 1 – 4Research Field Mathematics Years of Research Experience 1 – 4Additional InformationEligibility criteriaPhD in computer science/applied mathematics.
Demonstrable experience related to deep learning, including knowledge of the field and at least one successful implementation.
Motivated by a multidisciplinary environment (applied mathematics, soft matter physics, optics, cell biology), enjoying working in a team. Scientific communication is done in English. Speaking French is not mandatory.Website for additional job detailsWork Location(s)Number of offers available 1 Company/Institute Institut de génétique et développement de Rennes Country France City RENNES GeofieldContact CityRENNES WebsiteSTATUS: EXPIREDShare this page

Expected salary

Location

Rennes, Ille-et-Vilaine

Job date

Fri, 27 Dec 2024 05:28:55 GMT

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