Student Frontend Developer

Salary Competitive

Student Frontend Developer

Are you passionate about developing software with high focus on ease of use? Does the idea of working in a smaller AI start-up excite you?  Do you have trust in science, and do you want to join us in revolutionizing the speed of creating scientific evidence, fighting fake news, and increasing evidence-based innovation? Then you might be the student we are looking for!

We are looking for a Student Frontend Developer to become part of our development team at Silvi.ai.

 

Who is Silvi.ai? Silvi.ai is a software platform which summarizes scientific evidence in a fast and scientifically rigorous way using machine learning and artificial intelligence. More specifically, the Silvi.ai platform enables faster and fully updated systematic literature reviews to support evidence generation by scientists.

 

What will you do?

As Student Frontend Developer you will be part of our highly dedicated and skilled development team on-site in our Copenhagen office. You will support our joined effort in developing the Silvi.ai platform to become as easy to use as possible, while striking a balance between functionality and simplicity.

 

·       You will write high-quality, scalable, and reusable code & review the code of other team members.

·       You will support our work in optimizing Silvi.ai’s speed and scalability.

·       You will cooperate closely with our back-end developers.

·       You will debug errors, troubleshoot issues, and make performance optimizations.

 

Who are you?

  • You have a couple of years left of your studies as a software developer.

  • You may have experience with frontend development from other companies.

  • You have experience with frontend programming using JS frameworks such as Vue.JS or React.js and other tools such as Webpack, TypeScript or NPM.

  • You are motivated by improving user experience and helping the user reduce their manual workload by utilizing machine learning and natural language processing.

  • You are curious at heart and are interested in learning about new scientific domains (e.g., evidence based medical treatment of patients)

  • You are fluent in English and may speak Danish.

  • You live within commuting distance to our office in Islands Brygge, Copenhagen, and have a Danish working permit.

·        You are comfortable with the large amount of independence which comes from working in a start-up where everybody’s contribution is super important.

·        You love to laugh with your colleagues at the office.

 

We offer you:

·       10-20 hours a week

·       A company culture with huge freedom, no micromanagement, and 100% focus on results.

·       A company where we have a clear vision on ‘doing good’ by improving the availability of scientific evidence.

·       A "family first" company culture where a good work-life balance is a priority, with room for flexible hours around exams etc.

·       A diverse company at its core that celebrates all ages, genders, geographies, and qualifications.

 

Salary: Starting salary 170 DKK an hour, depending on your qualifications

Preferred start: as soon as possible.

Silvi.ai is based at Islands Brygge in Copenhagen, where you will be expected to spend most of your working hours. You can read more about Silvi here: silvi.ai

 

Application and contact

Send an application and a CV here on The Hub.

For further information about the job call CTO Rasmus Hvingelby at the number below.

Deadline for application: September 25th 2023

For more information or questions please contact us at dch@silvi.ai or phone number +45 61 28 96 94

Perks and benefits

This job comes with several perks and benefits

Near public transit
Near public transit

Free office snacks
Free office snacks

Paid holiday
Paid holiday

Remote work allowed
Remote work allowed

Social gatherings
Social gatherings

Free coffee / tea
Free coffee / tea

See all 10 benefits

Working at
Silvi.ai

Silvi is an end-to-end screening and data extraction tool supporting Systematic Literature Review and Meta-analysis. Silvi.ai was founded in 2018 by Professor in Health Economic Evidence, Tove Holm-Larsen, and expert in Machine Learning, Rasmus Hvingelby. The idea for Silvi stemmed from their own research, and the need to conduct systematic literature reviews and meta-analyses faster. The ideas behind Silvi were originally a component of a larger project. In 2016, Tove founded the group “Evidensbaseret Medicin 2.0” in collaboration with researchers from Ghent University, Technical University of Denmark, University of Copenhagen, and other experts. EBM 2.0 wanted to optimize evidence-based medicine to its highest potential using Big Data and Artificial Intelligence, but needed a highly skilled person within AI. Around this time, Tove met Rasmus, who shared the same visions. Tove teamed up with Rasmus, and Silvi.ai was created. Silvi uses AI to increase the speed of collecting and analyzing published data to created meta-analyses and systematic literature reviews. When using Silvi, the researcher still makes all the scientific decisions, but with AI supporting data extraction, the speed of doing meta-analyses increases immensely. Silvi is directly connected to literature engines to ensure that the results are always up to date. These core qualities of Silvi ensures a tool that quickly helps you create high quality evidence that stays relevant. Silvi helps create systematic literature reviews and meta-analyses that follow Cochrane guidelines in a highly reduced time frame, giving a fast and easy overview. It supports the user through the full process, from literature search to data analyses. Silvi is directly connected with databases such as PubMed and ClinicalTrials.gov and is always updated with the latest published research. It also supports RIS files, making it possible to upload a search string from your favorite search engine (i.e., Ovid). Silvi has a tagging system that can be tailored to any project. Silvi is transparent, meaning it documents and stores the choices (and the reasons behind them) the user makes. Whether publishing the results from the project in a journal, sending them to an authority, or collaborating on the project with several colleagues, transparency is optimal to create robust evidence.

Read more about Silvi.ai

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