Training stays at the IFT within the JAE-intro program

Training stays at the IFT within the JAE-intro program

The IFT is offering 8 projects within the CSIC JAE-intro program. This program offers 200 grants of 2500 euros for undergraduate students for training stays in the academic year 2018-19. The grants are intended to provide students with an initiation in research within CSIC institutes, through training stays of up to 4 months, some oriented towards TFG and TFM projects.

Each student can select one research topic of interest upon application, which is open from May 3rd to June 1st 2018.

See application form here

Questions regarding the CSIC JAE-Intro program can be addressed to dpe@csic.es
For questions regarding the IFT proposals, please contact severoochoa.ift@uam.es

The IFT has proposed 8 possible supervisors and topics, as follows:

JAEINT18_EX_0386: Beyond Einstein's General Relativity, theories and observations (supervisor: Savvas Nesseris)

 JAEINT18_EX_0390: Predictions for elementary particle masses (Supervisor: Sven Heinemeyer)

 JAEINT18_EX_0394: Signatures of primordial black holes as dark matter (Supervisor: Juan García-Bellido)

 JAEINT18_EX_0506: String theory and the swampland (Supervisor: Fernando Marchesano)

 JAEINT18_EX_0542: Improving the Standard Model of Particle Physics (Supervisor: Luca Merlo)

 JAEINT18_EX_0741: Holographic applications of supergravity (Supervisor: Oscar Varela)

 JAEINT18_EX_0747: Black holes and quantum information (Supervisor: José L. Fernández Barbón)

 JAEINT18_EX_0931: Gravitational waves from the early Universe (Supervisor: Guillermo Ballesteros)

Últimas Noticias


Nuevo vídeo en el canal de YouTube del IFT.


Las derivadas están por todas partes y sirven para todo: desde calcular la pendiente... más

El IFT celebra el reconocimiento, que pone de relieve la estrecha colaboración entre teoría y experimento, necesaria para impulsar el avance... más

El objetivo principal del programa es fomentar sinergias entre los dos grupos de Aprendizaje Automático (Machine Learning, ML) e... más