Research Inter In Quantum Machine Learning

Detalles de la oferta

Somos una empresa tecnológica que opera a nivel global.
Si te apasiona la tecnología y crees en su capacidad para transformar el mundo, ARQUIMEA es tu sitio.
¡Únete!
ARQUIMEA , we are a technology company operating globally and providing innovate solutions and products in highly demanding sectors.
Our areas of activity are Aerospace, Defense & Security, Big Science, Biotechnology and Fintech.
ARQUIMEA Research Center (ARC) , part of ARQUIMEA , was born in 2019 with the aim of inventing the technologies of tomorrow.
An environment of innovation and excellence at European level from which senior and junior researchers from around the world develop disruptive technologies and business models that will serve as an engine of socio-economic growth in the medium and long term.
We are looking for a  research intern who is pursuing a master's degree and is interested in developing their thesis on a project related to quantum machine learning applied to time-series forecasting.
Tasks to be performed:   Analyze the state of the art in quantum machine learning, with a special focus on time-series forecasting.
Develop novel quantum machine learning models and evaluate their performance.
Test the developed models against conventional machine learning algorithms.
Required skills, experience and candidate profile:   Python programming.
Bachelor's degree-level knowledge of artificial intelligence.
A bachelor's degree in engineering, computer science, physics or mathematics.
Currently pursuing a master's degree in a related field, such as artificial intelligence, quantum information, etc.
Additionally, we will also value experience in the following areas:   Basic knowledge of quantum physics.
Think Big, Do the Job & Enjoy Life At ARQUIMEA, we value diversity and inclusion.
We do not discriminate on the basis of race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, or other protected factors by law.
All candidates will be considered equally based on their skills and experience


Salario Nominal: A convenir

Fuente: Talent_Ppc

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