Call for applications: "Artificial Intelligence for the Sciences" doctoral program

The "Artificial intelligence for the Sciences" doctoral program is hosted by Université PSL with the support of the European program Horizon 2020 - Marie Skłodowska-Curie Actions-COFUND.

This unique, structuring and international project aims to create a research community from multiple PSL laboratories and schools, along with a dozen of private and public partners. AI4theSciences will co-fund for 26 doctoral fellowships on the interfaces of AI or massive data processing.

The future PhD fellows selected for the "Artificial intelligence for the Sciences" project will receive a specific training on their concentration and also benefit from weekly seminars and conferences to develop a set of skills in connection with AI and Machine Learning, writing popular science articles, Open Science, cross-disciplinary skills, etc.
Each doctoral student will benefit from a joint supervision: a supervisor by a PSL expert in the chosen subject, and a co-supervision by a specialist in AI techniques or big data – who may work for laboratory outside PSL or for a private partner located in France or in Europe.

Applications for PhD projects are open from November 17, 2020 to February 26, 2021. The winners will begin their doctoral project in Autumn 2021.

Requirements for applicants

• Applicants must hold a master’s degree (or be in the process of obtaining one) or hold a University degree equivalent to a European Master’s (5-year duration) when the call is closed;
• There are no requirements based on nationality or age, but applicants should not have lived or carried out their main activity (work, studies, etc.) in France for more than 12 months in the 3 years immediately before the deadline of the call (MSCA Mobility rule), namely between the 27th of February 2018 to the 26th of February 2021
• Applicants should be available to start the program on schedule.

The applicants should provide the following documents:

• Transcripts translated into English of the master’s degree (or equivalent 5-year degree). A copy of the master’s degree or a certificate of achievement will be required later on for the final registration;
• International resume and a cover letter explaining why the student wants to prepare a PhD, why they apply to this offer and their professional project (guidelines will be given to the applicants in order to help them in the writing of their letter);
• Two reference letters written by academics;
• A signed statement on the mobility rules, availability and conflicts of interest (the template available at the end of the guide for applicants).

Selection of applications

For the start of the 2021 academic year, 15 doctoral contracts, out of the 23 subjects listed below, will be jointly funded.

The future doctoral students of the program will be selected between from March and June 2021 in two rounds:

• Selection on the basis of the application package from March 15, 2021 to April 9, 2021 (round 1)
• Interviews with candidates from June 1 to June 25, 2021 (All candidates will be contacted in April 2021)

The excellence of the applicants - an essential principle of the Horizon 2020-MSCA projects - will lead to select the 15 PhD projects out of the 23 offered in the call. Out of the 23 projects open for application, 9 projects will therefore not be funded but may be submitted during the second AI4theSciences call for applications which will start in May 2021.

The 23 PhD subjects available for applications

• PhD project 1 : Transfer learning in biomechanics: high-dimensional transfer learning for personalized biomechanical modeling in surgery planning - application to anterior-cruciate ligament reconstruction (Mines Paris - PSL)
• PhD project 2 : AI-supported optimisation of multi-actor energy systems enhanced with privacy & confidentiality preserving data sharing (Mines Paris - PSL)
• PhD project 3 : Advanced methods for enhancing interpretability of AI tools with application to the energy sector (Mines Paris - PSL)
• PhD project 4 : Breaking the curse of high-dimensional PDE’S and applications to mathematical finance (Université Paris Dauphine - PSL)
• PhD project 5 : Dark energy studies with the Vera Rubin Observatory LSST & Euclid - Developing a combined cosmic shear analysis with Bayesian neural networks (Observatoire de Paris - PSL)
• PhD project 6 : The politics of coding (Ecole Normale Supérieure - PSL)
• PhD project 7 : Physics-Informed Machine Learning in the context of seismic imaging (Mines Paris - PSL)
• PhD project 8 : Physically Informed Machine Leaning for controlling unruptured intracranial aneurysms (Mines Paris - PSL)
• PhD project 9 : LIterary Success, Style and Artificial Intelligence (Ecole Normale Supérieure - PSL)
• PhD project 10 : Towards neuromorphic computing on quantum many-body architectures (ESPCI Paris - PSL)
• PhD project 11 : 3DMorphEmbryo: AI-assisted reconstruction of 3D human embryo morphology from 2D medical images to improve the prediction of its development potential (Collège de France)
• PhD project 12 : Data-driven Enzyme Evolution (ESPCI Paris - PSL)
• PhD project 13 : Machine learning for origin of life in the RNA world (ESPCI Paris - PSL)
• PhD project 14 : Artificial Intelligence for Seismic Hazard Monitoring with InSAR (Ecole Normale Supérieure - PSL)
• PhD project 15 : Impact of human cognitive traits on financial market formation (Ecole Normale Supérieure - PSL)
• PhD project 16 : Creating AI/ML techniques to enhance mechanistic eco-evolutionary computer simulations (Ecole Normale Supérieure - ENS)
• PhD project 17 : Language Acquisition in Brains and Algorithms: towards a systematic tracking of the evolution of semantic representations in biological and artificial neural networks (Ecole Normale Supérieure - PSL)
• PhD project 18 : Artificial Intelligence to Decode the Genomic Replication Programme of Human Cells (Ecole Normale Supérieure - PSL)
• PhD project 19 : Learning dynamics in biological and artificial neural networks (Ecole Normale Supérieure - PSL)
• PhD project 20 : Unsupervized learning of causal graphical models from time-resolved cell biology data (Institut Curie)
• PhD project 21 : Finding and classifying transient patterns to predict from EEG the depth of anesthesia (Ecole Normale Supérieure - PSL)
• PhD project 22 : A computational and artificial Intelligence approach for studying dolphin communication (Ecole Normale Supérieure - PSL)
• PhD project 23 : Machine Learning for biodiversity monitoring (EPHE - PSL)