Level of qualifications required : Graduate degree or equivalent
Fonction : PhD Position
About the research centre or Inria department
The Inria Sophia Antipolis - Méditerranée center counts 34 research teams as well as 8 support departments. The center's staff (about 500 people including 320 Inria employees) is made up of scientists of different nationalities (250 foreigners of 50 nationalities), engineers, technicians and administrative staff. 1/3 of the staff are civil servants, the others are contractual agents. The majority of the center’s research teams are located in Sophia Antipolis and Nice in the Alpes-Maritimes. Four teams are based in Montpellier and two teams are hosted in Bologna in Italy and Athens. The Center is a founding member of Université Côte d'Azur and partner of the I-site MUSE supported by the University of Montpellier.
The PhD project will take place in the environment of the new Inria-Inserm team COMPO (COMputational Pharmacology in Oncology), located in the pharmacy faculty of the University Hospital of Marseille. This team is composed of mathematicians, pharmacists and clinicians and is a unique multidisciplinary environment focused on developing novel computational tools for decision-making in clinical oncology.
This PhD subject aims at establishing and validating on clinical data mathematical, mecha- nistic models of metastatic apparition and development in cancer patients, by using statis- tical (machine) learning methods applied to clinical data sets.
Description of the project
Metastasis and associated complications are the cause of 90% of deaths from cancer. In breast cancer for instance, determining the extent of the residual metastatic disease following surgery is a major clinical challenge in order to personalize the adjuvant treatment. Nowadays, on top of classical demographic variables, several biological and molecular biomarkers predic- tive of metastatic relapse are measurable at diagnosis, including genetic expression signatures [van ’t Veer et al., 2002]. So far, these parameters have been included into survival statistical models but no mechanistic, biologically grounded mathematical model of metastasis has been validated on large data sets.
Based on previous work of mathematical modeling of metastatic development validated on pre- clinical data [Benzekry et al., 2016] and more recently on clinical data [Nicolo et al., 2020], the primary step will be to improve existing models of metastatic dynamics based on the biological mechanisms. Briefly, the model consists in a partial differential equation of transport type for description of a population of tumors, which depends on several patient-specific parameters for simulation of the metastatic development. Modeling of the effect of post-surgery therapy will also be developed in collaboration with oncologists and radiotherapists. The different tasks will be:
To refine previous work in relation to existing molecular classifications of breast cancer
To include dormancy in the breast cancer model
To extend previous results to new datasets
To study the use of deep learning algorithms for prediction of metastasis-free survival from high-throughput data
- To include and validate the effect of adjuvant therapy in the model
In order to do so, the intern will work on clinical data sets from collaborations with clinical oncologists. These include databases of: breast cancer (with respectively n=1057 and n=174 patients), lung cancer (n=350 patients) neuroblastoma (n=48 patients) and melanoma (n=212).
In addition, use of machine and deep learning algorithms from publicly available high-throughput data (genomics and imaging) will be investigated and combined with the previous mathematical model.
[Benzekry et al., 2016] Benzekry, S., Tracz, A., Mastri, M., Corbelli, R., Barbolosi, D., and Ebos, J. M. L. (2016). Modeling Spontaneous Metastasis following Surgery: An In Vivo-In Silico Approach. Cancer Res, 76(3):535–547.
[Nicolo et al., 2020] Nicol`o, C., Perier, C., Prague, M., Bellera, C., MacGrogan, G., Saut, O., and Benzekry, S. (2020). Machine learning and mechanistic modeling for prediction of metastatic relapse in early-stage breast cancer. JCO: Clinical Cancer Informatics, 4(4), 259–274.
[van ’t Veer et al., 2002] van ’t Veer, L. J., Dai, H., van de Vijver, M. J., He, Y. D., Hart, A. A. M., Mao, M., Peterse, H. L., van der Kooy, K., Marton, M. J., Witteveen, A. T., Schreiber, G. J., Kerkhoven, R. M., Roberts, C., Linsley, P. S., Bernards, R., and Friend, S. H. (2002). Gene expression profiling predicts clinical outcome of breast cancer. Nature, 415(6871):530–536.
Mechanistic modeling; metastasis; artificial intelligence; cancer
Main activities (5 maximum) :
- Reading biological and clinical literature
- Statistical data analysis
- Mathematical (mechanistic) modeling
Master of science in either applied mathematics, statistics, bioinformatics or theoretical physics.
Good programming level in either python (preferred), R or matlab
Good oral and written communication skills in English
- Subsidized meals
- Partial reimbursement of public transport costs
- Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
- Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage
Duration: 36 months
Location: Sophia Antipolis, France
Gross Salary per month: 1982€brut per month (year 1 & 2) and 2085€ brut/month (year 3)
- Town/city : Marseille
- Inria Center : CRI Sophia Antipolis - Méditerranée
- Starting date : 2020-11-02
- Duration of contract : 3 years
- Deadline to apply : 2020-10-30
- Inria Team : DIR-SOP
PhD Supervisor :
Benzekry Sébastien / Sebastien.Benzekry@inria.fr
Inria is the French national research institute dedicated to digital science and technology. It employs 2,600 people. Its 200 agile project teams, generally run jointly with academic partners, include more than 3,500 scientists and engineers working to meet the challenges of digital technology, often at the interface with other disciplines. The Institute also employs numerous talents in over forty different professions. 900 research support staff contribute to the preparation and development of scientific and entrepreneurial projects that have a worldwide impact.
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.