Background

Semiconductor Energy Laboratory (SEL) Co., Ltd., is the leading company in the development of crystalline oxide semiconductors for ultra-low power LSI applications. While high-quality, high-performance oxide transistors have been extensively demonstrated, there is a need to accelerate circuit and application development using these transistors.

Goal

The overall goal is to increase the development efficiency of LSI circuits using oxide semiconductor transistors. You will be expected to contribute to the improvement of current development processes and implement them in actual circuits.

Tasks

1. Review the literature on oxide semiconductor development workflow, circuit design methodology, and chip designs of past prototypes.
2. Identify issues specific to oxide semiconductor transistors in the current design workflow and chip designs.
3. Propose and implement improvements and evaluate their effectiveness.
4. Improve the efficiency of chip design using design and programming tools.
5. Demonstrate chips with shortened development time or chips with high efficiency using simulation tools and model chip designs.

Qualifications

• Experience of circuit design and electronic design automation (EDA) tools.
• Basic LSI circuit design and programming (Python, including machine-learning library).
• Microsoft Office
• Understanding of CMOS circuits, their limitations, and fundamental differences from oxide semiconductor circuits
• Willingness to overhaul established CMOS thinking to harness the potential of oxide semiconductors.
• Good communication skills in written and oral English, preferably also in basic conversational Japanese (English versions of tools and PCs are available).
• Good command of the latest trends in artificial intelligence (AI) and how it can be used in circuit design.

Contact information

This project is hosted by SEL. Students are invited to apply for a scholarship from SEL through the Application Form from 2024-03-15. For more information, please visit the SEL web site or contact the SEL public relations team at [email protected].

Background

The emergence of large-scale language models (LLMs) has led to significant developments in natural language processing. In particular, advances in understanding questions and fluently generating answers with LLMs have been remarkable. However, interactive sessions with LLMs in business are not easy, as it requires judging the truth or falsehood of seemingly correct answers. It is also known that LLMs are not good at answering questions regarding local information that is not generally known to the public. LLMs can be trained with local information but costs are high. Also, it is difficult to dramatically improve LLM performance from unstructured information retrieval. Therefore, a system configuration that obtains answers by supplementing information to an LLM from a database of non-public, local information, is effective.

Goal

We will build a system that receives questions in natural text, searches for appropriate data in a local database, and generates answers using an LLM. Considering methods for evaluating and ranking of search results and prompts for the LLM, the system will improve on current solutions to generate relevant answers.

Subjects

1.1 Retrieval processing using LLMs

1.2 Method for creating search queries from natural text necessary for retrieving supplemental local information for feeding into LLMs

1.3 Methods for evaluating and ranking search results.

2.1 Interactive, web-based interface development

2.2 Design of prompts for combining search results and the LLM

2.3 Display search results.

Qualifications

• Python, Linux, and Web app development.
• Knowledge of python libraries, especially Transformers and LangChain.
• Good communication skills in English and, preferably, also basic Japanese language skills.

Contact information

This project is hosted by SEL. Students are invited to apply for a scholarship from SEL through the Application Form from 2024-03-15. For more information, please visit the SEL web site or contact the SEL public relations team at [email protected].

Background

Smartphones and other portable electronics use rechargeable lithium-ion batteries, which include, among other components, positive and negative electrode materials, and an electrolyte. The electrolyte contains lithium salts, solvents, and additives. While there has been tremendous progress in Li-ion technology development, further improvements with respect to safety, charge density, and lifetime, is desirable. A fundamental major issue is the decomposition of the electrolyte due to the potential difference between electrodes. This issue can be addressed by forming a stabilizing thin film on the electrode surface through various electrolytes. However, the chemical reactions and effects of these electrolytes have not yet been clarified, so it is necessary to conduct experiments by making batteries with various electrolytes and measuring the material properties and battery performance to find optimal solutions.

Goal

The overall goal is to find an electrolyte that gives a battery with fire protection, higher charge density, and longer lifetime. You will gain detail understanding of the manufacturing processes in rechargeable lithium-ion batteries, and the electrolyte you develop may lead to patent applications and scientific publications.

Tasks

1. Discuss, plan, and decide the experimental conditions (with SEL staff).
2. Make batteries with various electrolytes and solution concentrations.
3. Measure and evaluate the battery properties.
4. Create a data base of results.
5. Consider the chemical reactions and effects of each material.
6. Repeat from 2.

Qualifications

• Experience from working with glove boxes and battery charge/discharge testing equipment.
• Adequate attention to laboratory safety; You will handle atmospherically unstable, flammable, and hazardous materials. You need to be very careful about safety.
• Bachelor’s degree in chemical engineering, knowledge of electrochemistry, organic chemistry, or equivalent.
• Programming skills such as Python or Excel macros for compiling data.
• Accuracy to input data into a defined format; you need it to determine experimental condition and to use the condition data.
• Good communication skills in English and, preferably, also basic Japanese language skills.

Contact information

This project is hosted by SEL. Students are invited to apply for a scholarship from SEL through the Application Form from 2024-03-15. For more information, please visit the SEL web site or contact the SEL public relations team at [email protected]