First, it aims to innovate in liquid cooling, water-saving or water-free cooling, and power supply and energy storage to overcome current limits, meet high-……
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Multimodal AU data infrastructure and quality pptimization. It ensures the stability and high availability of the system, optimizes the performance of online……
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Use kdb+ and q language for querying large datasets from the data warehouse. Note: Leave of Absence (LOA) may be required to take on the internship.…
10+ years experience in the technical field of expertise in design, implementation and/or commissioning. Stay current on emerging technologies, architectures,……
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Research Scientist Intern - Data Center AIOps & Infrastructure - Global Frontier Tech Recruitment Program - 2027 Start (PhD)
Singapore
Location:
Singapore
Team:
Hardware
Employment Type:
Intern
Job Code:
A236380
Responsibilities
We are looking for talented individuals to join us for an internship in 2027. PhD Internships at our Company aim to provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies.
PhD internships at Our Company provides students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and development events, and collaboration with industry experts.
Applications will be reviewed on a rolling basis - we encourage you to apply early. Please state your availability clearly in your resume (Start date, End date).
Team Introduction: The team is responsible for technical planning and management of built-to-suit and leased data center projects in Asia Pacific region, data center infrastructure technology standardisation and research and development, as well as promoting green energy and achieving carbon neutrality as part of our global roadmap.
Topic Content: As intelligent computing and the AIDC industry develop rapidly, data center rack power density continues to rise. Traditional infrastructure struggles with heat exchange efficiency, water-saving, and energy use. At the same time, large amounts of maintenance data are underused, and maintenance relies heavily on human experience, making it hard to meet the industry's quality and policy demands. This topic focuses on two main areas: technology innovation and smart operation. First, it aims to innovate in liquid cooling, water-saving or water-free cooling, and power supply and energy storage to overcome current limits, meet high-density power needs, and comply with carbon reduction and water-saving policies. Second, it builds an AI agent system for data center maintenance that uses large AI models to learn from vast, varied multimodal maintenance data. This system enables multiple AI agents to work together to automate everything from monitoring and diagnosis to repair, creating an intelligent loop to optimize the power usage effectiveness (PUE) and shifting maintenance from "reacting after problems" to "predicting and fixing them automatically". By combining new hardware technology with AI-driven maintenance, the project seeks to improve data center energy efficiency, reliability, and operation efficiency.
Topic Challenges: 1. Multi-technology collaborative innovation: Liquid cooling technology must overcome challenges in efficient heat transfer and system reliability. Water-saving cooling sources need to achieve low water-efficiency temperature (WET) and coordinate dry and wet cooling methods. Power supply, distribution, and energy storage must solve source-grid-load-storage matching issues and enhance full-process efficiency. Coordinating innovations across these areas is highly complex.
2. Multi-agent collaboration system design: A multi-agent cooperation framework is required for managing complex operation and maintenance processes, enabling end-to-end autonomous execution from monitoring and diagnosis to automatic repair. Integrating these technologies is highly challenging.
3. Intelligent PUE optimization closed loop: Intelligent control of HVAC and power systems should be based on time sequence prediction and reinforcement learning to surpass human expert-level optimization. This demands advanced algorithms and strong engineering implementation.
4. Root cause analysis of heterogeneous data: Large models must automatically identify fault root causes and build knowledge from massive heterogeneous monitoring data, requiring high model understanding and generalization capability.
5. Technology implementation and adaptation: Hardware innovation must comply with policies and fit industry needs, while AI operations must integrate with existing platforms and tools. Successfully combining and implementing these poses significant challenges.
Topic Value:
1. Solve key technical problems in data centers and increase global competitiveness.
2. Enable water-saving and low-carbon operation, ensuring data centers run efficiently, stably, and in compliance through AI-driven maintenance.
Qualifications
Minimum Qualification
1. Currently pursuing PhD in in Electrical Engineering, Thermal Engineering, Energy & Power, Materials, Refrigeration, Environmental Engineering, Mechanical Engineering, Computer Science, Automation, or related fields are preferred.
2. Possess excellent problem analysis and solving skills, an innovative and rigorous mindset, and the ability to independently overcome technical difficulties.
3. Possess independent research capabilities for theoretical and applied research. Familiar with liquid cooling, thermal management, hydrophilic coatings, renewable energy, and energy storage, keeping track of cutting-edge industry technologies.
Preferred Qualifications
1. Master professional knowledge in heat transfer, fluid mechanics, material characterization, and water treatment. Candidates with related papers, patents, research projects, or engineering commercialization experience are preferred.
2. Familiar with LLM principles and technology ecosystems. Candidates with engineering experience in large model applications or multi-modal content understanding are preferred.
3. Deeply understand AI Agent design concepts. Candidates with experience in independently developing Agent applications from 0 to 1 are preferred.
Job Information
About Us
Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content.
Why Join ByteDance
Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day.
As ByteDancers, we strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us.
Diversity & Inclusion
ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.