Student Assistant (Multiple Openings and Projects)

ESnet’s mission is to accelerate science by delivering unparalleled networking capabilities, tools, and innovations. ESnet interconnects the US National Laboratory system, is widely regarded as a technical pioneer and is currently the fastest science network in the world. We are a dynamic organization, highly motivated and focused on results. We are working at the leading edge of software-defined networking, network knowledge plane, dynamic network infrastructure, network visualization, network knowledge plane, multi-domain and multi-layer architectures, machine learning, and quantum network etc. The successful students will be the ones that bring strong and diverse coding skills and are self-motivated.

 

As part of the application process, please combine a short cover letter with your resume and explain which projects you would prefer to apply to.

 

Project One

Title: Machine Learning And Network Use Case Term: Spring/Summer 2023

Project Mentor: Mariam Kiran

Required Skills: Python, GUI programming, database, modeling, and simulation, machine learning library Abstract:

This project adds to the current research in the Self-Driving Network Group to help develop tools and resources that can be used for self-driving networks. We have traffic prediction challenges, parallel computing for machine learning, and similar tools that interface with network tools and protocols. If you are passionate about how machine learning can be applied to real-world problems in the networking space, this is the right project for you.

 

Project Two

Title: A Configuration Management System Case Study For Network Automation Term: Spring/Summer 2023

Project Mentor: Marc Koerner

Required Skills: Basic networking knowledge, software architecture, programming: python, java Abstract:

ESnet uses the Cisco Network Service Orchestrator (NSO) for configuration management across our networking devices. We have built networking services to automate the device configuration based on certain standardized operations. This project’s scope is to understand the basic automation concept in NSO and investigate potential open source alternatives, including feature analysis, a potential prototype service implementation, identifying performance metrics, and conducting measurements.

 

Project Three

Title: Anomaly Detection For Network Outage Risk Mitigation And Self-Healing Term: Spring / Summer 2023

Project Mentor: Marc Koerner

Required Skills: Networking knowledge, machine learning, programming: python, java Abstract:

Nowadays, networks are complex and rely on specific mechanisms or protocols to anticipate larger network outages in a failure situation. Machine learning-based anomaly detection is an emerging topic that could help to prevent outages in the first place. This project investigates certain network traffic anomaly classes and identifies the appropriate actions, including leveraging a software defined-networking controller or configuration management system in order to mitigate the risk or even actively triggering self-healing capabilities.

 

Project Four

Title: Building a 100Gbps HardwareIPv6 Translation Mechanism with FPGAs Term: Spring / Summer 2023

Project Mentor: Chris Cummings

Required Skills: Network Knowledge, Ability to understand RFCs, P4, and possibly python. Abstract:

SIIT-DC (RFC7755, also known as stateless NAT64) allows devices on IPv4-only network segments to communicate with IPv6-only devices. This project will work to develop a hardware implementation of RFC 7755 SIIT-DC protocol using the P4 programming language and Xilinx FPGAs. The project delivery will be an open source implementation that can translate high throughput elephant flows generated by and destined to equipment that cannot yet be upgraded to support IPv6.

 

Project Five

Title: ARTIQ-based Real-time Quantum Network Control Term: Spring / Summer 2023

Project Mentor: Wenji Wu, and Erhan Saglamyurek

Required Skills: Knowledge of Linux-based systems and networking concepts. Familiarity with open-source software development, Python programming, and scripting. Experience with the ARTIQ control system for quantum information experiments.

Abstract:

DOE/ASCR is currently supporting Berkeley Lab (LBNL), UC Berkeley (UCB), The University of Innsbruck, and Caltech for setting up a testbed for quantum networking technologies (QUANT-NET). The primary goal is to establish a three-node distributed quantum computing network between two sites, LBNL and UCB, connected with an entanglement swapping substrate over optical fiber and managed by a quantum network protocol stack. On top of this entanglement swapping substrate, the most fundamental building block of distributed quantum computing and quantum repeater by teleporting a controlled-NOT gate between two far trapped-ion nodes will be implemented.

The successful candidate will work with the research team to develop an ARTIQ-based real-time quantum network control capability for the testbed. The Advanced Real-Time Infrastructure for Quantum physics (ARTIQ) features a high-level programming language called ARTIQ Python. Experiment code will be compiled and executed on dedicated FPGA hardware, with nanosecond timing resolution and microsecond branching latency. Preference will be given to students with experience in ARTIQ and quantum physics.

 

Project Six

Title: Exploring Quantum Sensing in QUANT-NET Term: Spring / Summer 2023

Project Mentor: Erhan Saglamyurek, and Wenji Wu

Required Skills: Knowledge of the theory and experiment of optics and photonics, quantum communication, quantum optics, quantum sensing, device, system testing, and characterization. Abstract:

QUANT-NET is a quantum-network testbed comprising three nodes arranged to carry out distributed quantum information processing tasks by leveraging QUANT-NET’s capabilities of entanglement distribution, swapping, and routing over optical fibers managed by a quantum-network protocol stack. In addition to computing and communication, distributed quantum sensing based on entangled sensors represent another powerful paradigm that would endow new quantum-network capabilities.

The successful candidate will study distributed quantum sensing, explore the use of entangled sensors for the precision measurement of QUANT-NET channels and nodes to enhance, e.g., phase stability, synchronization, and frequency locking, in support of the quantum-network functionalities such as high-fidelity entanglement swapping and quantum teleportation. Also, the candidate will investigate noise mitigation for entangled sensors enabled by the error correction capability of QUANT-NET. As such, the study results will create a new avenue to carry out high-fidelity quantum-network protocols and advance distributed quantum sensing by introducing a noise-resilient mechanism underpinned by distributed quantum computing. Preference will be given to students with experience in 1) nonlinear and quantum optics experiments, 2) fiber optical communications, and 3) theoretical background in quantum information and computing. The successful candidate will focus on device and system-level theoretical and experimental studies of QUANT-NET in conjunction with various distributed quantum sensing protocols based on discrete and continuous variables. The candidate will generate a final report to elucidate distributed quantum sensing as a powerful tool and appealing application for quantum networks.

 

Project Seven

Title: Data Visualization of Network Measurement Data Term: Spring / Summer 2023

Project Mentor: Sartaj Baveja, Katrina Turner Requirements: Javascript, React, Data Visualization Abstract:

The Software Measurement and Analysis Team maintains the my.es.net portal and the Stardust instance of Grafana. This project will entail working with the SMA team to create new and maintain existing visualizations across platforms. Duties might include: creating new plugins to submit to Grafana’s Open Source Plugin Library, adding features to existing plugins, creating new and exciting visuals for the portal, adding features to existing visualizations on the portal, etc. If you are passionate about Data Visualization and looking for new, creative ways to help users analyze data more efficiently, we’d love to have you on board.

 

Project Eight

Title: Grafana Dash-n-Grab Term: Spring / Summer 2023 Project Mentor: Samir Faci

Required Skills: Go, familiarity with Github CICD is nice to have. Abstract:

Grafana Dash-n-grab is an open-source tool created at ESnet to provide an easy-to-use CLI to interact with the Grafana API. It allows users to back up and restore dashboards, data sources, and other entities to external locations. This project is an opportunity to contribute to the existing open source tool by assisting with current tickets and adding new features. Depending on the interest and skill set, there can be opportunities to contribute upstream to other projects, setting up the groundwork for the plugin system, among other tasks in our roadmaps. Opportunity to work with some cloud providers, packaging, etc. If interested in Go and OSS projects, please join us.

 

Project Nine

Title: SENSE Multi-Domain Network Automation, Orchestration and Monitoring Term: Summer 2023

Project Mentor: Xi Yang

Required Skills: Knowledge of computer systems and computer network concepts. Familiar with Linux; Proficient in Python. Proficient in Java and/or JavaScript

Abstract:

The SENSE project (http://sense.es.net ) is building smart network services to accelerate scientific discovery in the era of big data driven by Exascale, cloud computing, machine learning and AI. The project’s architecture, models, and demonstrated prototype define the mechanisms needed to dynamically build end-to-end virtual guaranteed networks across administrative domains, with no manual intervention. The successful candidate will work with the SENSE project team to develop network automation agents and orchestration portals for network device automation and telemetry. If you are interested in research work, network telemetry data modeling, automated performance analysis, and multi-domain troubleshooting can be additional tasks, welcome to apply for this project.

 

Project Ten

Title: Creating Customer-Defined Network Services Using The Surfnet Orchestrator Term: Spring / Summer 2023

Project Mentor: Nemi McCarter-Ribakoff

Required Skills: Programming python(django, flask), javascript(reactjs), docker Abstract:

Automated network configuration and management have made great strides in recent years. Automated processes are advanced enough that customers may potentially be able to provision and manage their resources with the assistance of automation tools. This project involves using the SURFnet Orchestrator to create workflows that empower customers to provision and manage their network resources, from subscribing to Physical Connectivity to instantiating Layer 3 service.

 

Want to learn more about Berkeley Lab’s Culture, Benefits and answers to FAQs? Please visit: https://recruiting.lbl.gov/

 

Notes:

• The Spring 2023 Term is 16 weeks (1/9/2023 – 4/28/2023). The Summer 2022 Term is 12 weeks (6/1/2023 – 8/24/2023). Student participation requires 20 hours per week commitment for Spring appointment, and 40 hours per week for Summer appointment. A “late start” date can be considered for academic reasons.
• The student assistant appointment can be renewed based upon satisfactory job performance, continuing availability of funds and ongoing operational needs.
• Students who participate in their school’s Co-Op programs can also apply.
• Salary will be predetermined based on student step rates.
• This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
• Work will be primarily performed at Lawrence Berkeley National Lab in Berkeley, CA or the Champaign, Illinois office, with a possibility of working remotely.

 

Based on University of California Policy – SARS-CoV-2 (COVID-19) Vaccination Program and U.S Federal Government requirements, Berkeley Lab requires that all members of our community obtain the COVID-19 vaccine as soon as they are eligible. As a condition of employment at Berkeley Lab, all Covered Individuals must Participate in the COVID-19 Vaccination Program by providing proof that vaccination requirements have been met or submitting a request for Exception or Deferral. Visit covid.lbl.gov for more information.

 

Berkeley Lab is committed to Inclusion, Diversity, Equity and Accountability (IDEA) and strives to continue building community with these shared values and commitments. Berkeley Lab is an Equal Opportunity and Affirmative Action Employer. We heartily welcome applications from women, minorities, veterans, and all who would contribute to the Lab’s mission of leading scientific discovery, inclusion, and professionalism. In support of our diverse global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.

 

Equal Opportunity and IDEA Information Links:

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