The role focuses on ensuring secure, reliable, and high-performance digital platforms that support scientific research, laboratory instrumentation, data platforms, and advanced computational workloads. Key Responsibilities Support and maintain HPC environments used for modeling, simulation, computational chemistry, materials science, bioinformatics,
We work to help life advance, and we are always looking for innovative people who can contribute to our mission. How about becoming part of our team? Location: Brasil (BR) - São Paulo - Indaiatuba Function:
Description : Responsibilities : We are seeking an experienced and Enterprise Data Architect to join our team. As an Enterprise Data Architect, you will shape and execute our data strategy, with a focus on building a robust data mesh platform.
We are looking for the right people — people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and
Minimum qualifications : - Bachelors degree or equivalent practical experience. - 4 years of experience in an applied research setting, or similar. - Experience in programming languages used for data manipulation and computational statistics (e.g., Python, R, MATLAB,
Company Description An enterprise client is seeking CFD & Aerodynamic Engineers to help train and evaluate next-generation AI systems by contributing real-world engineering expertise. This opportunity is offered by a leading AI data platform that enables organizations to
About XebiaWith over 20 years of experience, our global network of passionate technologists and pioneering craftsmen deliver cutting-edge technology and game-changing consulting to companies on the brink of transformation. Since 2001, we have grown from a
Work ScheduleStandard (Mon-Fri) Environmental ConditionsOffice Job Description Description Programmer Join Us as a Programmer – Make an Impact at the Forefront of Innovation The Programmer performs advanced bioinformatics programming activities for the statistical and computational considerations of