EARTHBRAIN aims to expand its capabilities in the field of Artificial Intelligence, leveraging the most recent advancements in the field to further improve its products and services.
You will be joining EARTHBRAIN’s rapidly growing AI division, part of the Data Value Creation Group. The group analyzes EARTHBRAIN’s challenges, identifies novel, innovative methods to leverage data to tackle them. The team conducts research, development and implementation both in-house as well as with our external partners, pushing the boundaries of what is possible in the construction industry.
Responsibilities
- Help identify the technical challenges in areas related to Smart Construction in EARTHBRAIN’s operations and the operations of our clients.
- Apply advanced mathematical concepts to develop and improve AI algorithms
- Work on optimization problems for construction site planning and resource allocation
- Collaborate with AI engineers, as well as other teams and departments within the company, to translate mathematical insights into practical solutions, as well as identify, propose, explore and create ways to tackle the challenges using AI, ML or optimization algorithms as per your professional expertise.
Requirements
- PhD or Master’s in Physics, Mathematics, or related field with strong focus on:
- Linear Algebra
- Statistics and Probability
- Optimization Theory
- Numerical Methods
- Strong programming experience in at least one language (Python preferred).
- Excellent analytical and problem-solving skills.
- Experience with data analysis and statistical modeling
- Strong mathematical intuition and ability to work with abstract concepts.
- Ability to understand research papers and translate insights into action.
Nice to haves
While not specifically required, tell us if you have any of the following.
- Experience with machine learning frameworks (PyTorch, TensorFlow)
- Experience with version control systems (Git)
- Knowledge of basic software development practices
- Background in any of:
- Optimization algorithms
- Control theory
- Dynamical systems
- Computational physics
- Scientific computing
- Previous exposure to AI/ML concepts
- Experience with civil engineering