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Post-Doctoral Research Visit F/M Postdoctoral position in Topological Data Analysis
Il y a 2 mois
The successful applicant will be integrated into the PreMediT project, whose aim is to develop new mathematical and computational tools for Precision Medicine (PM), with a particular focus on topological methods. The goal of PM is to tailor treatment according to patients' characteristics by reliably figuring out which patient will benefit from a given treatment and when to initiate, modulate or stop such a treatment. The characteristics of the data involved (multimodality, longitudinality, small size, sparsity, and partly categorical nature) pose some crucial challenges.
Mission confiée
We believe the aforementioned challenges can be addressed by integrating information about the geometric or topological structure of the data into the machine learning pipelines, notably by developing tools based on Topological Data Analysis (TDA) and more precisely multi-parameter persistent homology. The objective of the postdoc will be to develop such tools, either at the mathematical/foundational level, or at a more applied level.
Principales activités
The main tasks may include:
- Designing new computable invariants for multiparameter persistence modules;
- Designing new descriptors for multivariate/multimodal time series based on Topological Data Analysis, possibly in combination with other types of representations (based, e.g., on DL architectures);
- Enhancing existing DP or RL based methods to compute optimal treatment policies using the above descriptors;
- Building new models for data generation.
Compétences
We primarily seek profiles with a strong expertise in at least one of the following topics:
- mathematical foundations of TDA, in particular multi-parameter persistence theory;
- applications of TDA to time series data, in particular to multivariate time series;
- applications of TDA to healthcare data at large;
- interactions of TDA with statistics, in particular with causal inference.
Profiles with an expertise in related topics (e.g. application of deep learning methods to multimodal and/or longitudinal data) will be considered as well.
Avantages
- 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 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
Rémunération
2788€ gross/month
