Constructor is an all-in-one platform for education and research. With expertise in machine intelligence and data science, Constructor is built to cater to the needs of schools, higher education, corporate training, alternative credentials, and professional sports, offering solutions for teaching and administration, learning and research.
From infrastructure to applications, Constructor elevates learning experiences, empowers educators, and drives research breakthroughs.
Our headquarter is situated in Switzerland. Also we have entities in Germany, Bulgaria, Serbia, Turkey, and Singapore.
This is a part-time opportunity. Interns are not eligible for equipment.
We are seeking a highly motivated and talented student intern to join our dynamic team at Constructor Technology. As a student intern, you will have the opportunity to gain valuable hands-on experience in the EdTech industry while working alongside our experienced professionals.
In this role, you will assist our team in various software development, AI research or industry/market research and analytics projects. You will also have the chance to collaborate with cross-functional teams, contribute ideas, and learn from industry experts. This internship is an excellent opportunity for students to enhance their skills and kick-start their career in software development, AI research or market research.
Potential topics:
- Large Language Models for Protein Sequences:
The goal is to investigate how various token representations of the protein sequences affect the performance of the LLM models. The dataset is >100M protein sequences (1D strings) - Diffusion-based molecular docking:
The goal is to develop, implement and benchmark diffusion-based molecular docking. The dataset is ~10K atomic structures of protein-ligand complexes (3D molecular objects). - High-performance virtual screening of chemical properties for large-scale chemical libraries:
The goal is to implement fast retrieval from tabular data of 100K-1B size chemical libraries, given request on chemical property values.
Requirements for the projects:
- Currently enrolled as a student in CUB
- Strong analytical and problem-solving skills
- Python knowledge, incl. packages for ML (sklearn, tensorflow/pytorch)
- Data Science/AI algorithms knowledge
- Excellent problem-solving and communication skills
- Knowledge of molecular biology is an asset
- Excellent knowledge of operating with large databases is required for Task 3.
What We Offer
