AI Research Intern – New Position
Recently graduated or finalising your degree in Mathematics or Physics soon?
DiRoots is a rapidly growing team of researchers, engineers, and software developers heading up design automation and Artificial Intelligence. We are currently working on two exciting projects that will be a game-changer for the AEC industry, and we need other great minds in the team.
Your job will be focused on following areas: deep learning, machine learning, control systems, simulation, optimisation, and knowledge representation applied to diverse areas such as geometry, design exploration, design automation for engineering or construction practices. This is initially a home-based position.
- Research, develop and document mathematical models for developers to implement
- Collaborate with researchers and developers in the team
- Participate in brainstorming sessions and come up with innovative ideas
- Read relevant scientific papers and perform literature reviews
- Evaluate existing algorithms and reproduce results on specific datasets
- Explore, prototype and develop new AI agents and machine learning models and techniques
- Introduce creative approaches to research topics and generates new approaches, perspectives and solutions to research topics
- Being a recent graduate (or becoming soon) in a field related to Computer Science, Mathematics or Physics
- Excellent math skills (e.g., Linear Algebra, Probability, Statistics, Calculus)
- Background and experience in one of the following: Artificial Intelligence, Machine Learning, Deep Learning and/or Data Science
- Good communication skills and an awareness of how to communicate data and results effectively
- Comfortable working in newly forming ambiguous areas where learning and adaptability are key at times, the ability to lead and rally stakeholders and team members
Preferable experience (but not mandatory)
- 3D graphics/3D geometry manipulation/computational geometry
- Knowledge Representation (semantic models, graph databases, etc.)
- Experience with at least one of the DL platforms (TensorFlow, Keras, PyTorch, etc.)
- Familiarity with Deep Learning techniques (e.g., Network architectures; regularisation techniques; learning techniques; loss-functions; optimisation strategies, etc.)