Masters Internships
Every year 10 Masters-level student Internship Projects on data science will be funded (typical funding scale: €3,500). The projects should be interdisciplinary, and advance the state of the art in terms of novel designs/solutions/systems/results related to data science and data intelligence. This action will be coordinated with the relevant MSc programs of the partner institutions, but will also be open to students from other universities, in order to ensure a high-quality cohort of interns. The interns will have the opportunity to collaborate with researchers from different disciplines, and gain experience on real research problems.
2022 Call for proposals (closed)
The diiP institute will support interdisciplinary projects that advance the state of the art in terms of novel designs/solutions/systems/results related to data science and data intelligence. Thanks to additional financing, diiP will support projects related to fairness of AI algorithms and to detection/analysis of disinformation (a.k.a. fake news).
The diiP institute will pay the stipend of the intern (as specified by the university), for a period of up to 6 months (up to €3,500). The internships should take place between January-August of the following calendar year.
The leader of the project (principal investigator) must be affiliated with one of the diiP partner institutions: Université Paris Cité, SciencesPo, Université Sorbonne Nord, and INED. Collaborations among partner institutions and synergies with other interdisciplinary IdEx institutes at the Université Paris Cité are encouraged.
This call is now closed.
2022 second call for proposals (closed)
The diiP institute has the possibility to fund some extra Masters projects for 2022. If you have not submitted an application to our first call, you can now apply until October 29, 12 noon (Paris time).
Please follow the guidelines and instructions on how to apply.
This call is now closed.
2024
Deep learning-based prediction of protein-carbohydrate interactions
Tatiana Galochkina ➔
2024
Automated segmentation and clustering of spICP-ToF-MS time series
Mickael Tharaud ➔
2024
DNA methylation in patients: A new meta-analysis of EPIC data across borders
Maud De Dieuleveult ➔
2024
Identification of image circulation by AI in large collections of historical photographs
Daniel Foliard ➔
2024
Deep learning for estimating gas concentration maps from satellite or airborne hyperspectral images
Andrés Almansa ➔
2024
Blind Image Deblurring via Latent Diffusion Models
Andrés Almansa ➔
2024
Investigating Diffusion Models for Astronomical Image Deconvolution – boosting the synergy between Euclid and LSST
Alexandre Boucaud ➔
2024
Biomarker prediction from images of histological slides of cancerous tissues
using modern AI techniques: comparisons of different neural architectures
Nicolas Loménie ➔
2024
Compact representations to detect gravitational waves from extreme-mass ratio inspirals
Quentin Baghi ➔
2024
Towards design of protein knottin using deep learning
Jean-Christophe Gelly ➔
2024
Exploring the similarities of a large bank of protein pockets in a perspective of
multiple protein-ligand interactions prediction
Anne-Claude Camproux ➔
2024
Deep Mendelian Randomization: explaining causality between different hereditary traits at genome-wide scale
Marie Verbanck ➔
2024
Modeling conditioned place preference test for evaluation of addictiveness of substances: toward experimental design optimization & smart data analysis
Emmanuel Curis ➔
2024
Diffusion Models Based Visual Counterfactual Explanations
Valerie Mezger ➔
2023
OpenStreetMap and Sentinel-2 data for the production of environmental indices for demographic studies
Sylvain Lobry ➔
2023
Mining molecular dynamics open data
Pierre Poulain ➔
2023
Prediction of protein-carbohydrate binding sites using deep learning methods
Tatiana Galochkina ➔
2023
Exploration of press articles related to Covid-19 at the European level within the Covid-19 Museum
Yves Rozenholc ➔
2023
Machine Learning for Photometric redshift estimation of LSST galaxies
Simona Mei ➔
2023
Deep learning to model genetic pleiotropy to understand the human genetic architecture
Marie Verbanck ➔
2023
Generalization of a method enabling to update vineyard geographic databases from satellite data
Camille Kurtz ➔
2023
Diffusion Models Based Unpaired Image-to-Image Translation to Reveal Subtle Phenotypes
Valérie Mezger ➔
2023
Enhancing earthquake location with domain adapation
Leonard Seydoux ➔
2022
Monitoring the seismic activity of Mayotte through image processing of fiber optic signals
Lise Retailleau ➔
2022
Automatic detection and location of hydro-acoustic signals linked to Mayotte submarine eruption
Jean-Marie Saurel ➔
2022
Investigating regulatory B cell differentiation and their therapeutic effect in neuroinflammatory disease through single cell analyses and computational biology
Simon Fillatreau ➔
2022
Transcriptomic Analysis using Intensive Randomization
Dorota Desaulle ➔
2022
Random projections for the reduction of gravitational wave template banks
Eric Chassande-Mottin ➔
2022
“Search for features in astrophysical objects close to cosmic neutrinos”. An indirect approach to cosmic neutrino association with astrophysical objects
Yvonne Becherini ➔
2022
Multiple imputation for heterogeneous biological data
Matthieu Resche-Rigon➔
2022
Tracking auto-immune diseases in electronic health record
Maud De Dieuleveult ➔
2022
Modeling genetic pleiotropy using machine learning to understand the human genetic architecture
Marie Verbanck ➔
2022
Combining visual and textual information for enhancing pathologic case retrieval systems in radiological practices
Florence Cloppet ➔
2022
Veracity assessment framework for discovering social activities in urban big datasets
Soror Sahri ➔
2022
Deep Learning-based EEG Epilepsy Detection and Analysis
Jerome Cartailler ➔
2021
Inferring cultural transmission of reproductive success through machine learning methods
Frédéric Austerlitz ➔
2021
Large image time series analysis for updating vineyard geographic databases
Camille Kurtz ➔
2021
Smoothing of incomplete air pollution regions of interest from satellite observations
Laurent Wendling ➔
2021
Combining visual and textual informations for enhancing image retrieval systems in radiological practices
Florence Cloppet ➔
2021
Automatic production of environmental indicators from freely available remote sensing data: from a global to a local scale
Sylvain Lobry ➔
2021
Digital Pathology: when AI meets with anatomo-pathology
Nicolas Loménie ➔
2021
Machine learning model of volcanic lava properties helps understanding the dynamics of volcanic eruptions
Charles Le Losq ➔
2021
ComplexNeuroViz: Complexity Visualisation for Neural Machine Translation
Nicolas Ballier ➔
2021
Machine learning for the study of EEG data recorded during general anesthesia
Laurent Oudre ➔
2021
Influence of blood pressure and aqueous humor dynamics on the response to glaucoma medication: a data-driven computational study
Marcela Szopos ➔
2021
Machine Learning techniques applied to eye movement analysis for early screening of learning disorders in young children
Zoï Kapoula ➔
2021
Artificial Intelligence for source deblending in the next generation of astrophysical big data imaging surveys – Combining Euclid and LSST
Marc Huertas-Company ➔
2021
Malvasia – MAchine Learning to VAlue Single Interferometer Analysis
Agata Trovato ➔
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