Intern - Microelectronics Algorithms, Software Scaling

About the role

The internship focuses on estimating the scaling of different algorithms and software used in Machine Learning and Scientific Applications. Students will analyze state-of-the-art Large Language Models like ChatGPT, Gemini, and Llama, among others, and research their scalability and complexity for various applications such as time series, sensing, natural language processing using transformers, and convolutional neural networks. This experience aims to bridge expertise in algorithm and software development with real-world applications for scientific purposes.

Responsibilities

• Identify different algorithms and software, including those ported to CPUs, GPUs, and Application-Specific Integrated Circuits (ASICs).
• Develop metrics for measuring algorithmic scaling and complexity.
• Outline the nature and quantity of data required for each hardware platform, collaborating with the mentor.
• Conduct data analysis to ensure the quality and validity of the data.
• Develop models for estimating energy usage for the problems at hand, under mentor guidance.
• Carry out verification, validation, and critical analysis of the estimates.
• Refined and developed models to integrate scientific knowledge into model formulation and training phases.
• Prepare reports and scientific publications detailing the advancements under the mentor’s supervision.

Requirements

Eligible candidates must have a background in Physics, Electrical Engineering, Computer Engineering, or Computer Science, and be pursuing a Master's or Doctoral degree. Strong communication skills, collaborative abilities, and passion for innovative solutions in Science and Engineering are essential. Prior experience with Python programming is beneficial.

Qualifications

Candidates should be at least 18 years old, currently enrolled in an educational program or recently graduated, and possess US work authorization. They should also demonstrate commitment to personal responsibility, value for environment, safety, and security, and be able to communicate effectively with colleagues and clients.

Skills

Strong analytical skills, proficiency in Python programming, and experience with data analysis and modeling are required. Familiarity with scientific computing and machine learning concepts is beneficial.

Benefits

Growth and mentorship from experienced engineers and scientists at SLAC and Stanford University. A supportive, interdisciplinary, and collaborative work environment. Opportunities to engage in multidisciplinary research across computer engineering, physical sciences, applied mathematics, and software applications.

Pay and Schedule

The expected pay range for this position is $31.02 - $39.26 per hour. The internship lasts for 12 weeks, starting between May and mid-August, contingent on the candidate's availability.

Schedule

The internship consists of estimating energy usage in computing systems based on published data and research. The intern will work closely with the mentor to identify relevant algorithms, software, and hardware platforms, conduct data analysis, and develop models for energy estimation.