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Looking for new exciting job opportunities?

If you are passionate, open minded, self starter, creative and innovative, we would love to work with you!

Come join us and you will be working among other young and enthusiastic entrepreneurs in an incubator in the centre of Barcelona.

Check our Job offers, and send us your CV and a motivation letter that helps us to know you better.

If there is nothing for you, send a mail to info@sycaitechnologies.com

Prácticas - Desarrollo de interfaz gráfica en java y html

Prácticas

R&D

Buscamos actualmente un estudiante para dar soporte al equipo técnico en el desarrollo de gráficos para un software de diagnóstico precoz de cáncer de páncreas.

Las tareas del equipo consistirán en el desarrollo de una interfaz gráfica para la gestión de una base de datos, botones, menús y gráficos y en la creación de un entorno de validación automática de aplicaciones basadas en java y/o html.

Se busca un perfil independiente y proactivo cursando grado o master en informática, audiovisuales, desarrollo de videojuegos o similar con experiencia en desarrollo con java y html (se valora experiencia en mysql). LEER MAS...

Intern - Business development and strategy

Internship

Business development

We are looking for an intern to support in the business development team, collaborating in market studies and fundraising activities. The student will participate in the definition of the escalation strategy of Sycai Technologies in close contact with the founders of the company. Experience with market studies, pricing strategies and benchmark analysis is desired.

Knowledge in medical device market or AI-based software for diagnosis will be valued.  READ MORE...

Intern - Clinical trial design and analysis

CLOSED

We are looking for a biostatistician trainee or similar with experience in data analysis on biomedical research and statistical software knowledge.
Applicants are required to have successfully completed a degree majoring in statistics, or an equivalent qualification, have an aptitude for advanced mathematical work, a high-level knowledge of statistical concepts and methods, and extensive experience in the use of statistical software packages. The candidate will have experience in data analysis of different type of databases and will face to several biomedical. READ MORE...

Intern - Developer of DL based software for medical imaging

CLOSED

We are looking for a student that can support the development of semantic segmentation deep-learning based frameworks to find cysts, nodules and other lesions on CT scans and magnetic resonance images of the abdomen. The student will learn by doing all the tools and resources available for the development of neural networks and will investigate the state-of-the-art led by our experienced technical team.

Experience with Python, Tensorflow, Pytorch, etc. is required. The candidate shall be willing to work in a young, dynamic and entrepreneurial environment.

Developer of DL based software for medical imaging analysis

CLOSED

The worker will develope semantic segmentation deep-learning based frameworks to find cysts, nodules and other lesions on magnetic resonance images of the abdomen. This development shall be based on the state-of-the-art DNAS (differentiable neural architecture search) methodology. Proven experience in medical imaging, data analysis, docker and one of the following deep learning frameworks is mandatory: tensorflow, pytorch, keras or chainer. Studies is mathematics, physics, engineering or equivalent are desired. The candidate shall be willing to work in a young, dynamic and entrepreneurial environment. READ MORE...

AI Researcher - Organ semantic segmentation

Researcher

Computer vision

The main objective of the researcher's work is the creation of a framework for automatic neural network design based on the state-of-the-art NAS and DNAS methods (neural architecture search), able to create light and integrable networks for the semantic segmentation of different cystic lesions in abdominal CT scans. Moreover, it is requested the development of a statistical prediction model, that correlates the performed segmentation with key factors of the patient's clinical record to predict the cysts' evolution. READ MORE...