Description
ABOUT DEEP SCIENCE VENTURES
Deep Science Ventures (DSV) is a venture creator combining available scientific knowledge and founder-type scientists into high-impact ventures to build a future where both humans and the planet thrive. DSV operates in 4 sectors: Agriculture, Climate, Pharmaceuticals and Computation, tackling the challenges defining those areas by taking a first-principles approach and partnering with leading institutions.
ABOUT THE ROLE
In 2023, DSV is launching Deep Science Ventures College to exponentially increase the number of people solving the world’s hardest problems through our first accredited training program, the Venture Science Doctorate. We will be building on DSV's proven process of identifying and addressing reasons for failures in key science-driven areas from climate change mitigation and cancer to heterogeneous compute. To date, this has been a long and manual process which limits how rapidly we can address these challenges and how fast any science-driven company can move. With the recent advancements in transformers, semantic search and learning analytics, we see a path to massively accelerate and scale this work to give not only our team but all researchers superhuman powers and, in time, to reduce the cost of science to near zero. We have demonstrated the key principles in-house and are looking to build a team to optimise and productise this work and help us scale to take on hundreds of thousands of challenges.
KEY RESPONSIBILITIES
- Create the best environment to integrate relevant information (publications, reports, conversations, patent data etc.) to fastest, highest quality progress towards scientific outcomes.
- Plan user research, cognitive work/task analysis, behaviour analysis and usability testing
- Develop UI mockups, process flows and prototypes that clearly illustrate how products function and look like
- Design and implement new ways of interacting with AI models and systems in the context of scientific text
- Create trustworthy conversational flows and tune for machine-to-human interactions
- Connecting the outputs of venture scientist learning analytics to UX design requirements
- Collect and analyse qualitative and quantitative data on how humans understand the capabilities of AI systems.
Requirements
- Obsessed with building delightful products with experience in scaling from the first few users to hundreds of thousands of users
- Have experience with web app technologies (HTTP servers, databases, javascript/typescript, React, etc.) and experience iterating quickly and writing production-quality code.
- Ability to design (Figma, Adobe Suite) and implement user interfaces for initial prototypes and, in time, build out a full UI team.
- Comfortable across the entire product management stack - defining success, writing specs, talking to users, running analytics, prioritising feature work, managing releases, etc.
- Experience developing majority text-based interfaces would be a strong advantage.
- Data-driven analytical mindset focused on helping our users move science faster.
Good to have
- Experience with language models (professionally or personally) or machine-learning-centric tools more broadly
- Experience building tools for researchers
- Interest in research on learning, e.g. cognitive task analysis
Benefits
- Competitive salary;
- Flexible working environment (remote or hybrid);
- Rapid personal development and massive learning curve;
- Working with some of the most ambitious and impact-driven individuals you'll ever find;
- Help build the next generation of hard tech ventures.
