Exciting Part-Time Opportunity for Data Science Students! (40-80%)
MDPI Introduction
A pioneer in scholarly open-access publishing, MDPI has been supporting academic communities since 1996. Our mission is to foster open scientific exchange in all forms and across all disciplines.
We operate more than 400 diverse, peer-reviewed, open-access journals, supported by over 35,500 academic editors. We serve scholars from around the world to ensure the latest research is openly and broadly available.
Team Introduction / Position
To strengthen our AI team and the Technology Innovation department, we are looking for a working student in Data Science.
This is a part-time position based in our city center office in Basel, Switzerland.
As a Data Science Student, you will be responsible for assisting with the development, experimentation, and creation of machine learning, statistical, and advanced mathematical algorithms for various applications, focusing on NLP, Graph Machine Learning, or LLM models.
You will also support the analytics team by analyzing data and developing business dashboards for management.
Tasks & Responsibilities
- Support the AI team in developing applications in the areas of NLP, LLM, and Graph Machine Learning.
- Develop, optimize, and evaluate new machine learning and statistical models.
- Explore new approaches and algorithms to solve specific business problems.
- Research and compare prototype solutions.
Requirements
- Currently enrolled as a BSc or MSc student in Computer Science, Data Science, Statistics, Mathematics, or Physics.
- Theoretical and technical knowledge of machine learning and deep learning algorithms.
- Proficiency in Python, including statistical and machine learning libraries (knowledge of other programming languages, such as R, is a plus).
- Ability to create dashboards using Streamlit or Shiny is a plus.
- Experience with deep learning development frameworks (PyTorch, TensorFlow) is beneficial.
- Experience in applying and implementing NLP and / or Graph Machine Learning is advantageous.
- Strong verbal and written communication skills, with the ability to articulate, document, share, and present ideas and results to both technical and non-technical audiences (fluency in English is required).
- A creative team player with a results-oriented mindset.
- Strong analytical thinking skills.
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