Contract type : Public service fixed-term contract
Level of qualifications required : Graduate degree or equivalent
Fonction : PhD Position
About the research centre or Inria department
The PhD student will be supervised at CEA Leti by Dr. Cédric Allier (HDR) and Dr. Lionel Hervé (HDR) and by Dr. Sergei Grudinin at Inria. It will evolve in an environment at the interface between optical instrumentation, digital processing and cell biology. This thesis will therefore offer the possibility of following a solid training in applied research with a strong transversality. The skills of the doctoral student in digital processing will be in depth and the successful work will open opportunities in the field of biomedical imaging.
Pour une meilleure connaissance du sujet de recherche proposé :
At CEA-Leti, we are developing lensfree microscopy for the monitoring of cell culture. This technique overpass several limits of conventional microscopy (compactness, field of view, quantification, etc.). Recently we showed, for the first time, 3D+time acquisitions of 3D cell culture with a lens-free microscope. We observed cells without any labelling within the volume as large as several cubic millimeters over several days. This new mean of microscopy allowed us to observe a broad range of phenomena only present in 3D environments. However, two drawbacks are still present on the microscope prototype: a long reconstruction time (>1 hour/frame) and the reconstructed volumes present artefacts owing to the limited number of angular acquisitions. The thesis work will focus on the ability of deep learning technologies to overcome the above-mentioned limitations. Basically, a convolutional neural network will be trained on the basis of simulated 3D cell culture volume (ground truth) and simulated response of our current 3D lensfree microscope (input). This approach is expected to accelerate the reconstruction process and to allow full 3D reconstructions. Yet it poses two scientific questions: are simulated data pertinent to train a neural network and how can we assess the quality of 3D reconstruction obtained through a neural network?
- [Nature Photonics 2013] Mudanyali, et al. (2013). Wide-field optical detection of nanoparticles using on-chip microscopy and self-assembled nanolenses. Nature photonics, 7(3), 247.
- [Nature Scientific Reports 2018] Berdeu et al.. (2018). Lens-free microscopy for 3D+ time acquisitions of 3D cell culture. Scientific reports, 8(1), 16135.
- [U-NET] RONNEBERGER, et al.. U-net: Convolutional networks for biomedical image segmentation. In : Int. Conference on Medical image computing and computer-assisted intervention. Springer, Cham, 2015. p. 234-241.
- [CARE] M. Weigert, et al. “Content-aware image restoration: pushing the limits of fluorescence microscopy,” Nat. Methods, p. 1, 2018.
- [ref NN-SPEED] Rivenson et al. (2018). Phase recovery and holographic image reconstruction using deep learning in neural networks. Light: Science & Applications, 7(2), 17141.
Main activities :
- development of novel algorithms
- writing source code
- constructing benchmarks with synthetic data
- validation of methods on real data
- writing technical reports and scientific manuscripts
Profile of the candidate:
- Engineering degree in applied mathematics or physical sciences.
- Strong knowledge in image processing with skills in deep learning.
- Subsidized meals
- Partial reimbursement of public transport costs
- Leave: 5 weeks and 3 days of annual leave + 24 extra days off due to RTT (statutory reduction in working
- hours) + possibility of exceptional leave (sick children, etc.)
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage
Salary (before taxes) : 2050€ gross/month for 1st and 2nd year. 2100€ gross/month for 3rd year.
- Theme/Domain :
Optimization, machine learning and statistical methods
Scientific computing (BAP E)
- Town/city : Grenoble
- Inria Center : CRI Grenoble - Rhône-Alpes
- Starting date : 2019-10-01
- Duration of contract : 3 years
- Deadline to apply : 2019-06-30
Inria, the French national research institute for the digital sciences, promotes scientific excellence and technology transfer to maximise its impact. It employs 2,400 people. Its 200 agile project teams, generally with academic partners, involve more than 3,000 scientists in meeting the challenges of computer science and mathematics, often at the interface of other disciplines. Inria works with many companies and has assisted in the creation of over 160 startups. It strives to meet the challenges of the digital transformation of science, society and the economy.
Instruction to apply
Defence Security :
This position is likely to be situated in a restricted area (ZRR), as defined in Decree No. 2011-1425 relating to the protection of national scientific and technical potential (PPST).Authorisation to enter an area is granted by the director of the unit, following a favourable Ministerial decision, as defined in the decree of 3 July 2012 relating to the PPST. An unfavourable Ministerial decision in respect of a position situated in a ZRR would result in the cancellation of the appointment.
Recruitment Policy :
As part of its diversity policy, all Inria positions are accessible to people with disabilities.
Warning : you must enter your e-mail address in order to save your application to Inria. Applications must be submitted online on the Inria website. Processing of applications sent from other channels is not guaranteed.