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Sciber

Intelligent tools for efficient research and development

Why is it important for science to be effective?

Primary outcome of quality scientific research is a product with high added value bringing new potentials to affect our daily lives.

Multiple scientific teams around the globe work on the same or similar topics with limited collaboration.

Complexity of scientific challenges require deep background knowledge which may limit participation of individual scientists or smaller scientific teams in top level research due to insufficient resources, both personal and financial.

How to help scientists to work more efficiently

Effective research management helps to create and maintain resources with focus on their efficient utilization in achieving desired scientific outcome. It also attracts and motivate young talents to pursue their future career in science and research.

Collaboration and knowledge exchange within the research team is managed through access to live research data and notes taken by researchers during conducted experiments.

Open knowledge sharing with selected researchers or whole scientific teams can be achieved altogether with intellectual property and data ownership is secured.

State of the art IT solutions are implemented to help researchers to with designing experiments and evaluating results.

Presented scientific tool applies machine learning and AI to support scientists with drafting applications for grant schemes as well as evaluating applications upon their submission.

Our mission

Sciber's goal is to devise tools which would make scientific processes more efficient. We try to achieve this by finding solutions which would comply with following criteria:

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Simplicity

Simple tools are usually easier to create and when built they are usually more available than their more complex analogues.

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Universality

Universal tools can be applied in more processes thus potentially having impact on greater variety of scientific fields.

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Openness

Scientific results could be achieved faster if resources, data and ideas would be shared globally. On the other hand, greater number of participating investigators usually leads to more careful scrutiny of achieved results.

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Adaptability

The tools are expected to be adaptable to requirements which may emerge in the future and are unknown at the time when the tools were designed.

Our team

Sciber is a Dublin based startup established by Slavomíra Husarová and Patrik Florek. Both its founders worked for several years as investigators in scientific laboratories. After switching their career paths to different directions they remain passionate propagators of science and all the good stuff it generates.

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Slavomíra Husárová

Founder and CEO

Slavomíra studied microbes in clouds using nuclear magnetic resonance spectroscopy and currently works as a clinical research manager.

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Patrik Florek

Founder and CTO

Patrik investigated bacterial death and these days is mostly interested in machine learning, cellular automata and web technologies.

Contact us

Are you interesting in learning more about this project? Send us a message and we will be in touch very soon.