Bss&msc Internship: Ai for Big Science - Bremen, Deutschland - Constructor group
vor 2 Wochen
Beschreibung
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.
Our headquarter is situated in Switzerland. Also we have entities in Germany, Bulgaria, Serbia, Turkey, and Singapore.
The "AI for Big Science" research team is at the forefront of integrating advanced artificial intelligence and machine learning techniques with cutting-edge scientific research.
Our team is dedicated to pushing the boundaries of what's possible in big science by leveraging AI to tackle some of the most challenging problems facing researchers today.
We are offering a unique internship opportunity for students to gain hands-on experience working alongside leading scientists and AI experts on real-world research projects.
As an intern with the "AI for Big Science" team, you will:- Work on interdisciplinary research projects at the intersection of AI/ML and various scientific domains.
Motivation:
This is a part-time opportunity. Interns are not eligible for equipment.
Requirements:
- Currently enrolled in an undergraduate program related to Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Solid skills in data processing and machine learning.
- Proficient in Python, with handson experience in using ML frameworks such as PyTorch or TensorFlow.
- Familiarity with packages for efficient computations like NumPy is essential.
- Strong problemsolving abilities and a collaborative spirit.
Potential Projects:
Develop Algorithms for New Probabilistic Computing Hardware:
Interns will have the opportunity to work on cutting-edge probabilistic computing systems.
This involves developing algorithms designed to leverage these systems for enhanced computing performance, especially in tasks involving uncertainty and prediction.
Design Knowledge Graph with LLMs:
This project aims to create expansive knowledge graphs using large language models (LLMs).
Interns will explore techniques to structure vast amounts of data in an interpretable, accessible way, enabling deeper insights across various domains.
Design LLMs Capable of Logical Reasoning:
Design Models for Assessing Knowledge Graph Evolution:
This project focuses on assessing how knowledge graphs grow and change over time.
Interns will develop models to track and predict the evolution of knowledge within these graphs, informing strategies to keep them current and relevant.
Design Physics Interpretation Models:
Interns will delve into the world of theoretical and applied physics to design models capable of interpreting complex physical phenomena.
Develop Methods for Monitoring Flying Vehicle Composite Hull Integrity:
In this cutting-edge project, interns will work on developing AI-based methods for real-time monitoring of the structural integrity of composite hulls in flying vehicles.
This encompasses designing sensors, data processing algorithms, and predictive models to ensure the safety and reliability of next-generation aviation technology.
How to Apply:
Please submit your resume, a cover letter highlighting your relevant experience and your interest in the internship, and any coding or project samples relevant to the internship's requirements.
Join us to advance the boundaries of big science with AI, contribute to meaningful scientific progress, and build the foundation for a remarkable career in research.
