Internships

Internships

Internships help students to consolidate the knowledge they acquire during their studies, but also to acquire experience by applying their knowledge to real problems. We are working on several important research problems related to current scientific challenges, which oftentimes need interdisciplinary work, and in which the students can get involved.

We are always looking for enthusiastic students to work with us. You can find below the list with currently available positions.

 

Internship_Innovation


2023

 

Stage M2
Scalable Subsequence Similarity Search in Seismic Time Series
Yoann Cano, Thémis Palpanas

 


2022

 

Stage M2
Active Learning for Neuroscience Time Series Analysis with Deep Learning
Qitong Wang, Stephen Whitmarsh, Jerome Cartailler, Thémis Palpanas

 


2021

 

Stage M2
Automatic Detection and Location of Hydro-acoustic Signals
Jean-Marie Saurel, Lise Retailleau, Valérie Ferrazzini, Clément Hibert, Thémis Palpanas

 

Stage M2
Veracity Assessment Framework for Discovering Social Activities in Urban Big Datasets
Philip Brandt and Soror Sahri

 

Stage M2
Explanation Methods for Multivariate Time Series Classification
Themis Palpanas and Paul Boniol

 

Stage M2
Deep Learning-based Prediction of Query Answering Ties for Data Series Similarity Search
Themis Palpanas and Qitong Wang

 

Stage M2
Deep Learning-based EEG Epilepsy Detection and Analysis
Themis Palpanas and Qitong Wang

 

Stage M2
An Indirect Approach for Neutrino Associations with Astrophysical Objects using Deep Learning and Statistical Inference
Yvonne Becherini and Themis Palpanas

 


2020

 

Stage M2
Data Series Analytics and Deep Learning for Gravitational Wave Glitch Detection
Themis Palpanas and Kostas Zoumpatianos

 

Stage M2
Compressed-memory Mapped-vectors Using Traditional and Deep Neural Network Compression Algorithms
Themis Palpanas and Kostas Zoumpatianos

 


2019

 

Stage M2
Signature-Based Disaggregation of Electricity Demand
Ioana Ileana and Themis Palpanas

 

2018

 

Stage M2
Machine Learning for Massive Data Series Collections
Themis Palpanas

 

Stage M2
Machine Learning for Recommendations and Profile Modeling in Social Networks
(2 positions)
Themis Palpanas

 


2017

 

Stage M2
Time Series Analysis for Near-Infrared Spectroscopy Data
Judit Gervain, Themis Palpanas

 

Stage M2
Very Large Time Series Analysis for Predictive Maintenance
(2 positions)
Themis Palpanas, Niklas Boers

 


2016

 

Stage M2
Gestion de l’incertitude et de l’incohérence de données dans le fusion de Big Data
Salima Benbernou, Mourad Ouziri

 

Stage M1/M2
Time Series Analysis of Human Eye Movement Data
Themis Palpanas, Zoi Kapoula

 

Stage M1/M2
Time Series Analysis for Near-Infrared Spectroscopy Data
Themis Palpanas, Judit Gervain

 

Stage M1/M2
Parallelization for Ultra-Fast Data Series Indexing
Themis Palpanas

 

Stage M1/M2
Ultra-Fast Visualizations for Data Series Analytics
Themis Palpanas

 

Stage M1/M2
Advanced Analytics: Mining All Lag-Correlated Data Series
Themis Palpanas