Full-Time
Lighting Technician
Lawrence Berkeley National Laboratory
5,001-10,000 employees
Fundamental science enabling energy and environment
Compensation Overview
$47.88/hr
No H1B Sponsorship
Berkeley, CA, USA
In Person
 Building Trades (1) |
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- Demonstrated experience in performing lighting fixture/lamp maintenance.
- Must possess all the qualifications and skills of a journey-level lighting technician (5 year apprenticeship and minimum of 3 years at journey level, total of 8 years.
- Perform routine interior/exterior lighting maintenance, washing, relamping, repairs, and retrofits.
- Rewire fixtures; replace ballasts, dimmers, igniters, capacitors, lamp holders, switches, and low-voltage lighting controls on 120V, 277V, and 480V systems.
- Install and retrofit LED, fluorescent, and H.I.D. lighting systems, including sensors and photocells, to meet sustainability standards.
- Troubleshoot lighting system malfunctions and adjust brightness, color temperature, and lens types to client needs.
- Perform Life Safety preventive maintenance and repairs for emergency lighting, exit signs, and ELDD compliance.
- Replace exterior poles/lights at varying heights and operate lifts, scissor lifts, boom trucks, and hand/power tools safely.
- Read blueprints, follow verbal/written instructions, attend safety meetings, and comply with all policies and safety procedures.
- Create and complete work orders, job logs, material quotes, training requirements, and accurate time reporting using Maximo and LETS systems.
- Knowledge of LBNL Facilities layout, key personnel, procedures governing stores issues, safety program, and facilities design requirements.
Berkeley Lab is a national research facility that conducts unclassified basic science across many fields, funded by the U.S. Department of Energy and managed by the University of California. Its work aims to address energy and environmental challenges by using interdisciplinary teams and building advanced tools for scientific discovery. Researchers study biosciences, computing sciences, Earth and environmental sciences, energy sciences and technologies, and physical sciences. The lab hosts about 4,200 scientists, engineers, staff, and students on a 200-acre site near UC Berkeley, and it has earned many prestigious honors, including Nobel Prizes and national academy memberships. Its goal is to generate foundational science that leads to practical, transformational solutions for energy and environmental issues while training the next generation of scientists and engineers.
Company Size
5,001-10,000
Company Stage
Grant
Total Funding
$2M
Headquarters
Berkeley, California
Founded
1931
Get referred to Lawrence Berkeley National Laboratory
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Simplify's Take
What believers are saying
- DOE awarded Berkeley Lab three industrial innovation projects on March 12, 2026.
- The Buildings Sector Scenarios dataset reached Nature in 2026, guiding grid and building planning.
- Genesis Mission financing expanded Berkeley Lab's AI and quantum workload across 30 partner projects.
What critics are saying
- DOE's FY2027 budget justification proposes a 20% cut to Berkeley Lab.
- Internal 2025 layoffs already hit research and operations after federal funding cuts.
- Congressional approval decides FY2027 cuts, and unresolved funding keeps layoffs and project cancellations alive.
What makes Lawrence Berkeley National Laboratory unique
- Berkeley Lab led 13 Genesis Mission projects on July 22, 2026, spanning AI science.
- Its QubiC platform with NVIDIA connected real-time GPU-QPU control by March 18, 2026.
- The lab combines federal user facilities, UC management, and 200-acre scientific infrastructure.
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↑ 3%Predicting microelectronics performance with physics-informed artificial intelligence. Aug 06, 2026 A new AI framework will link atomic-scale defects to device performance, helping researchers detect failures earlier and design more reliable, efficient electronics. (Nanowerk News) How a microelectronic device performs depends on what it is made of, how well its materials and interfaces are built and how electricity, heat and tiny defects change over time. These devices power much of modern life - from smartphones and laptops to secure communications and artificial intelligence (AI) hardware. As next-generation devices become smaller, faster and more tightly packed, their performance is affected more and more by tiny flaws in materials and interfaces. These defects can lead to overheating, electrical leakage, unreliable switching and, in the end, shorter device lifetimes. But defects are not always harmful. They can also influence electrical and thermal behavior in useful ways, depending on how they are distributed and how they evolve over time. Understanding both the harmful and beneficial effects of defects is essential for designing better microelectronics. To address the challenges defects pose, researchers at the U.S. Department of Energy's (DOE) Argonne National Laboratory, Lawrence Berkeley National Laboratory (Berkeley Lab), Oak Ridge National Laboratory (ORNL) and Northwestern University plan to develop the Materials Discovery Cloud. The project will create a physics-informed AI framework that learns how material composition, structure and operating conditions influence defect evolution and key functional properties such as electrostatic potential, current density and temperature. From protein folding to device function. AlphaFold is an AI system developed by Google DeepMind that predicts a protein's 3D structure based on its amino acid sequence. It transformed biology by making structure prediction much faster and more accurate, helping scientists better understand how proteins work. The new microelectronics effort follows a similar idea but applies it to a very different problem. Instead of predicting protein structure from sequence, the team aims to predict how networks of defects form, change and affect how a device works. "In biology, AlphaFold learned to connect sequence to structure," said Subramanian Sankaranarayanan, Argonne scientist and lead principal investigator on the project, as well as a professor at the University of Illinois Chicago. "We want to connect defect distributions in materials and interfaces to the electrical and thermal properties that matter for microelectronics. Such a framework remains elusive." Why defects are so hard to understand. Defects are tiny irregularities in a material's structure. They can include missing atoms, dislocations, voids or chemical disorder. Some defects hurt performance. Others can help enable useful behavior. The challenge is knowing which defects matter, when they matter and how they change under real operating conditions. These attributes are difficult to determine because no single instrument can capture the whole picture. Some tools, such as electron microscopes, can directly image features at very small scales. X-ray methods can reveal strain, buried structures and defect motion. Other techniques measure chemistry, electrical behavior and heat flow. Each method shows one part of the story, but not the whole system. A useful way to think about it is like trying to understand the day's weather from the temperature alone. Temperature tells you something important, but you also need to factor in wind, clouds, precipitation and humidity to see the full picture. The same is true for microelectronics. Bringing many tools into one framework. To close that gap, the team is combining many types of data from DOE Office of Science user facilities and advanced computing systems, drawing information from different tools and scales into one unified platform. At Argonne, those include the Advanced Photon Source and the Center for Nanoscale Materials for X-ray and microscopy measurements, as well as the Argonne Leadership Computing Facility for large-scale computing. Partner capabilities include the Advanced Light Source, the Molecular Foundry and the National Energy Research Scientific Computing Center at Berkeley Lab, and the Center for Nanophase Materials Sciences at ORNL. The Materials Discovery Cloud will help researchers gather experimental data, run simulations and generate synthetic data that mimic experiments. The synthetic data is especially important because complete experimental data sets for material samples are still complicated and time-consuming to collect. Simulations can fill in missing pieces and help train the AI framework. Another part of the effort focuses on autonomous discovery, which uses AI, machine learning and robotics to help researchers decide which measurements to run next and collect new data more quickly. That can help address one of the project's key challenges: generating enough high-quality experimental data to build and refine AI models. In this work, researchers are developing an AI-guided platform for microelectronics materials that can synthesize samples and carry out multiple kinds of characterization in a more integrated, high-throughput workflow. By reducing the need to move samples among facilities for separate measurements, the approach could speed data collection and help fill important gaps in the multimodal datasets used to train the framework. "What makes the Materials Discovery Cloud powerful is that we can bring together experiments, simulations and AI in one workflow," Sankaranarayanan explained. "That gives us a way to learn from limited data today while building a framework that can grow more capable as new data comes in." AI guided by physics. This system is not designed to be a black box that gives answers without explanation. Instead, it will be built around well-established laws of physics. This helps ensure the AI's predictions are grounded in how materials and devices actually behave. That certainty is important because the researchers want the system to do more than spot patterns in data. They want it to help reveal why certain defects lead to specific changes in performance, reliability or lifetime. To do that, the framework will combine several kinds of AI tools that can bring together many types of data, learn from both experiments and simulations and identify which new measurements would be most useful next. In the end, the goal is to connect tiny, atomic-scale features in a material to the larger electrical, thermal and mechanical behavior of a real device. What success could look like. If successful, the Materials Discovery Cloud could change how scientists design and test new materials and devices. Instead of waiting through long rounds of experiments, researchers may be able to get useful answers from a smaller set of early measurements. That could help them spot problems sooner, avoid spending time on weak candidates and focus more quickly on the most promising designs. Over time, the framework could also support inverse design. Rather than starting with a material and seeing how it performs, they could start with a goal - such as better heat management or a longer-lasting device - and ask what kind of material structure or defect pattern would be needed to achieve it. By bringing many different measurements into one predictive system, the effort aims to help scientists better understand, control and design the materials behind the next generation of microelectronics.
DOE selects four Texas A&M AI projects for Genesis Mission. TL;DR - Key Takeaways * Texas A&M landed four projects in DOE's Genesis Mission, spanning critical minerals, particle accelerator operations and nuclear reactor safety. * Two teams will use multimodal AI to improve mineral exploration, combining geological, geochemical, microbial, hydrological and satellite data. * Agentic digital twins could help scientists maximize costly beam time by recommending equipment settings, monitoring sensors and detecting problems. Four Texas A&M research teams have been selected for the U.S. Department of Energy's Genesis Mission, where they will develop and test AI systems for critical mineral research, particle accelerator operations and nuclear reactor safety analysis. The projects are part of the Genesis Mission's recently announced initial research portfolio, drawn from what DOE called its largest response ever to a funding opportunity. This includes 278 projects involving 342 institutions, with universities leading 168 of them. The work is organized around 26 national science and technology challenges DOE identified in February, including fusion energy, quantum computing, chip design and advanced manufacturing. DOE said the teams will gain access to the initiative's shared platform of AI agent frameworks, advanced models, industry software and high performance computing resources at national laboratories and partner facilities. That infrastructure is central to the Genesis Mission's premise of connecting AI with the scientific data, supercomputers and research facilities scientists already use to help them move more quickly from experiments to results. DOE has set a goal of doubling the productivity and impact of U.S. research within a decade through faster data analysis, better use of scarce computing and laboratory resources, and greater coordination across research institutions. At Texas A&M, two of the four projects will apply multimodal AI to critical minerals. A team led by civil and environmental engineering professor Kung-Hui Chu will work with Lawrence Berkeley National Laboratory to combine microbial, hydrological and geochemical data to build AI tools for locating mineral deposits and studying biological methods of recovery. A second team, led by geology and geophysics professor Nicholas Perez, will analyze geological, geochemical, geophysical and satellite data to identify patterns associated with rare earth deposits. The researchers will study Texas, the Colorado Mineral Belt and other parts of the Southwest in collaboration with Pacific Northwest National Laboratory. Another project, led by Texas A&M assistant professor Jonas Karthein in collaboration with MIT's Laboratory for Nuclear Science, will test agentic digital twins at precision nuclear physics facilities, where data is limited and beam time can cost hundreds to more than $10,000 per hour. The system will learn how equipment behaves, recommend settings, monitor sensors and flag problems, helping researchers make better use of scarce experimental time. The team plans a nine-month proof of concept at Texas A&M and MIT, with possible expansion to larger facilities in a second phase. A fourth project will explore AI support for reactor safety and licensing. Headed by nuclear engineering professor Yang Liu, the SHIELD system will help run reactor models and simulations and prepare documents for regulatory review. The team will test it on a sodium-cooled reactor design and conventional large light-water reactors. DOE cautioned that the selections are subject to award negotiations and do not yet guarantee funding. But projects like these could give the Genesis Mission concrete measures of progress, including better mineral exploration decisions, more efficient use of beam time and faster preparation of reactor safety analyses. Their results could also help show where AI can make the greatest impact across scientific research.
eXoZymes selected for doe's Genesis Mission to advance ai-powered digital twins for cell-free biomanufacturing. * Company to collaborate with Lawrence Berkeley National Laboratory on AI-enabled digital twins designed to accelerate optimization of enzyme-driven manufacturing processes. * The 9-month project awarded approximately $747,000 in total funding, including $147,000 awarded to eXoZymes * Expands eXoZymes' AI strategy beyond enzyme engineering into AI-guided manufacturing, leveraging digital twins to predict, optimize and accelerate development of cell-free bioprocesses. * Provides access to the DOE Genesis Mission Platform, including advanced AI models, AI agents and high-performance computing infrastructure to accelerate future platform development. LOS ANGELES, July 23, 2026 (Newswire.com) - Today, eXoZymes Inc. (NASDAQ:EXOZ) ("eXoZymes") - a pioneer of AI-enhanced enzymes that transform abundant feedstock into valuable nutraceuticals and novel medicines, - announced it has been selected to participate in the inaugural U.S. Department of Energy (DOE) Genesis Mission, a nationwide initiative bringing together leading researchers, national laboratories and industry leaders to accelerate scientific discovery through artificial intelligence. As part of the nine-month project, eXoZymes will collaborate with Lawrence Berkeley National Laboratory (LBNL) researchers Dr. Edward Baidoo and Dr. Hector Garcia Martin to develop AI-powered digital twins for cell-free biomanufacturing. The award also provides access to the Genesis Mission Platform, including advanced AI models, AI agents, and high-performance computing resources. CEO of eXoZymes, Michael Heltzen, states: "For centuries, biology has largely been an observational science. We believe the next generation of biomanufacturing will be built at the intersection of artificial intelligence and digital insights into biology. To make that happen, we are accelerating the design-build-test-learn cycle of biomanufacturing development using our cell-free platform." Heltzen continues, "In my opinion, digital biology - including digital twins - has the potential to become one of the defining technologies of this century, and projects like the Genesis Mission help accelerate that transition. Digital twins have already transformed industries by allowing engineers to simulate, optimize, and refine complex systems, like airplanes in the aviation industry, before building them in the real world. We believe the same transformation is coming of age in biology, where AI-powered digital twins could fundamentally change how biological manufacturing processes are designed, optimized, and scaled." Under the project, eXoZymes will generate curated experimental datasets from multiple cell-free enzymatic pathways, while Dr. Edward Baidoo's team will establish advanced metabolomic workflows that transform those experiments into AI-ready datasets. Dr. Hector Garcia Martin's team will then integrate those datasets into hybrid digital twin models that combine enzyme kinetics, reactor physics and machine learning, creating predictive models capable of identifying optimal operating conditions before laboratory validation. "Our cell-free platform generates exceptionally clean, quantitative datasets because it eliminates many of the biological variables inherent in living-cell systems," said Dr. Paul Opgenorth, co-founder and VP of Development at eXoZymes, who also is the Principal Investigator for the project. "That makes it an ideal foundation for training predictive AI models and building digital twins capable of optimizing increasingly complex biochemical manufacturing processes." The Genesis Mission generated the largest response to a funding opportunity in DOE history, with 278 projects selected across national laboratories, universities, companies, and nonprofit organizations. Selected research teams receive access to the Genesis Mission Platform, including advanced AI models, AI agent frameworks, and high-performance computing resources to accelerate scientific discovery. About eXoZymes Founded in 2019, eXoZymes is pioneering a cell-free biomanufacturing platform that uses AI-enhanced enzymes - called exozymes - to make valuable natural products and new analogs outside living cells. The company's platform is designed to replace inefficient extraction and petrochemical processes with a scalable way to produce high-value molecules for nutraceutical and pharmaceutical markets. eXoZymes is building a portfolio of biosolutions across NCT, cannabinoid analogs, santalene, and other high-value natural product molecules, with potential commercialization paths that include partnerships, licensing and joint ventures. Learn more at exozymes.com eXoZymes Safe Harbor This press release includes forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements, which are based on certain assumptions and describe the company's future plans, strategies and expectations, can generally be identified by the use of forward-looking terms such as "believe," "expect," "may," "will," "should," "would," "could," "seek," "intend," "plan," "goal," "project," "estimate," "anticipate," "strategy," "future," "likely," "potential," or other comparable terms, although not all forward-looking statements contain these identifying words. All statements other than statements of historical facts included in this press release regarding the company's strategies, prospects, financial condition, operations, costs, plans and objectives are forward-looking statements. Actual results could differ materially for a variety of reasons. You should carefully consider the risks and uncertainties described in the "Risk Factors" section of eXoZymes' quarterly reports on Form 10-Q, annual reports on Form 10-K, and other documents filed by eXoZymes from time to time by the company with the Securities and Exchange Commission. These filings identify and address important risks and uncertainties that could cause actual events and results to differ materially from those contained in the forward-looking statements. Forward-looking statements speak only as of the date they are made. Readers are cautioned not to put undue reliance on forward-looking statements, and eXoZymes assumes no obligation and does not intend to update or revise these forward-looking statements, whether as a result of new information, future events, or otherwise. eXoZymes does not give any assurance that it will achieve its expectations. eXoZymes contact Lasse Görlitz, VP of Comms & IR (858) 319-7135 [email protected] LinkedIn | X | YouTube
New federal dataset and $67M in BTO funding reshape how operators plan for building energy demand. The DOE's Building Technologies Office (BTO) is reshaping building energy demand planning by deploying over $67 million in R&D funding for 2024. Additionally, Lawrence Berkeley National Laboratory and the National Renewable Energy Laboratory have released a comprehensive county-level energy demand dataset extending through 2050. This initiative aims to enhance the strategies of operators in anticipating and handling future energy needs. This story was produced through MarketScale. See how Energy teams put it to work with Customer Stories & Case Studies. By MarketScale Newsroom · July 20, 2026, 1:44 PM PDT · Department of Energy Building Technologies Office Lawrence Berkeley National Laboratory National Laboratory of the Rockies Learn this in 60 seconds Key facts, context, and what it means, in one minute. Key takeaways Lawrence Berkeley and NREL have released a new county-level energy demand dataset through 2050. $67 million in funding has been deployed by the DOE's BTO for 2024 R&D. The initiative aims to help operators plan better for future building energy demands. A retrofit approach tested in a 184-unit multifamily building cut up-front electrification costs by 33% to 54% compared to standard methods. That single figure, published by the U.S. Department of Energy as part of its 2024 Building Technologies Office recap, illustrates the scale of the operational opportunity now in front of energy and facilities teams managing large real estate portfolios. More than $67 million in BTO funding deployed in 2024. The DOE's Building Technologies Office directed its 2024 investments across five major programs. The largest was the Building Energy Efficiency Frontiers and Innovation Technologies program, known as BENEFIT, which committed $38.8 million across 25 projects in 17 states. According to the Department of Energy, the combined BENEFIT cohorts from 2022, 2023, and 2024 carry a potential $40 billion in annual energy cost savings, assuming at least one project per technology area reaches mass adoption. The BENEFIT focus areas span next-generation building envelope systems, lighting, and HVAC, the three end uses that consistently dominate commercial and multifamily energy spend. For procurement and facilities directors evaluating which technologies to pilot, the 25-project portfolio represents a useful forward indicator of what will be commercially available in the next three to five years. BTO also pushed $6.5 million through its Small Business Innovation Research and Small Business Technology Transfer programs, funding 18 projects across 13 states in two separate award rounds, per the Department of Energy. An additional $2.4 million funded the Equitable and Affordable Solutions to Electrification prize, where the multifamily retrofit benchmark emerged. The Buildings Upgrade Prize, at $22 million, rounded out the major allocations, with 45 winners across 32 states selected in Phase 1 alone. A new dataset gives planners county-level demand visibility through 2050. On the planning side, researchers from Lawrence Berkeley National Laboratory and the National Laboratory of the Rockies published the Buildings Sector Scenarios dataset in Nature this year. The dataset, funded by BTO, provides hourly electricity demand projections at the county level across the entire contiguous United States through 2050, segmented by sector and end use. Non-electric fuel projections are also included at the state and annual level. The paper's authors, led by Jared Langevin of Lawrence Berkeley's Building and Industrial Energy Systems Division, describe the dataset as a response to high uncertainty in U.S. energy load growth, its effects on generation mix, and the downstream impact on customer costs. The dataset is designed to be customizable, letting utilities, grid operators, and large commercial energy buyers build their own scenarios rather than relying on a single forecast. For grid-connected facility operators, the practical value is in the hourly county-level resolution. That granularity supports site-specific analysis of peak demand exposure, a direct input to demand charge management strategies and onsite storage sizing decisions. The researchers validated the dataset against historical surveys and existing projected estimates of buildings sector demand, according to Nature. What the data and funding pipeline mean for operators today. The convergence of active federal R&D investment and a new public planning dataset shifts the operational calculus for energy and facilities teams. BENEFIT-funded technologies entering commercialization over the next several years will arrive in a market where utilities and grid planners are already using county-level scenario data. Operators who align their retrofit and electrification roadmaps with those same datasets will be better positioned in utility incentive programs and rate negotiations. The multifamily cost benchmark from the EAS-E prize is worth examining directly. A 33% to 54% reduction in up-front retrofit costs, demonstrated in a real 184-unit building and published by the Department of Energy, gives portfolio managers a credible reference point when building business cases for building-wide electrification. Most financial models for electrification retrofits have used rough estimates; this benchmark is based on an actual demonstrated approach. The Buildings Sector Scenarios dataset is publicly accessible and reproducible, per Nature, meaning operations teams with analytical capacity can run custom projections for their specific geographies and building types without waiting on utility-provided forecasts. Lawrence Berkeley and the National Laboratory of the Rockies also documented the full analysis workflow, which lowers the barrier for in-house energy analysts to adapt the tool. Featured companies The MarketScale Newsroom reports on the companies, technologies, and trends shaping 16 B2B industries. It turns primary sources and expert commentary into clear, useful coverage for the people doing the work.
Times argus Community News for July 15, 2026. * Jul 15, 2026 AROUND TOWN ScotDance competition. Charlotte Stone, 20, of Bradford, and Katherine Levasseur, 35, of Hinesburg, will compete in the ScotDance USA National Championship Saturday, July 25, in Dallas, Texas. The national championship, known as the United States Inter-Regional Championship, is the "Superbowl" of Scottish highland dance only open to those who qualified in the preliminary regional events. Dancers qualify by placing in the top three overall in their respective age group at the regional championship events, of which there are six around the United States. Stone and Levasseur competed at the East Region Championship April 25 in St. Leonard, Maryland, hosted by the Southern Maryland Celtic Festival. Stone placed 2nd Runner-Up in the 18 and Under 22 age group and Levasseur placed 2nd Runner-Up in the 22 and Over age group. The five-day ScotDance event will host dancers from across the United States, Canada and Scotland, in open competitions, choreography, dance challenges, and the North American championship. In the championship event, dancers are given set, championship steps to perform and are judged individually. They will compete in the four Highland dances: the Highland Fling, Sword Dance, Seann Triubhas, and Strathspey & Reel of Tulloch. Stone is a student/assistant teacher of, and Levasseur is owner/instructor at, Highland Dance Vermont training dancers in traditional Scottish technique. Intro to Highland classes are available this fall in Waterbury and Essex; learn more at highlanddancevt.com. Vermont weavers. RANDOLPH - The Vermont Weavers Guild welcomes everyone to hands-on workshops and presentations of hand-weaving and related fiber arts. Typically held at White River Craft Center in Randolph, morning presentations and activities are free to the public but donations are welcome. Remote attendance by Zoom can be arranged. Workshops require advanced registration and payment. More detailed information and how and when to register for workshops is available at www.vermontweaversguild.org. The Vermont Weavers Guild membership starts at $30 for new members' first year. Information on current and past programs, other activities, membership benefits can also be found at the website. MILITARY NEWS Veteran's Place. NORTHFIELD - Veteran's Place in Northfield, an 18-bed transitional housing facility, announced a first-of-its-kind clean energy modernization project in partnership with Lawrence Berkeley National Laboratory, to improve comfort, safety and health outcomes for veterans at the facility. When complete, the new system will reduce or eliminate heating and domestic hot water costs thereby lowering operating expenses, and provide central air conditioning in residents' rooms for the first time. Currently, there are 16 formerly unhoused, male veterans at the facility. LBNL designed the full system concept and has provided all the major components, including heat pumps, thermal storage tanks and metering equipment. Veteran's Place is responsible for hiring electricians and plumbers to install the system and provide components needed to finish the system installation. They are seeking community donations to help complete installation and ensure this transformative system becomes operational. Estimated funds needed to complete the project range from $30-40,000. Donations can be made at www.Vermontveteransplace.org. Composting course. Registration is now open through Sept. 4 for University of Vermont Extension's short course on backyard composting, "From Food Scraps to Soil," a six-week hybrid course where soil scientists and composting experts teach participants how to transform food scraps and yard waste into nutrient-rich compost that improves garden and landscape soils. The course runs from Sept. 11 to Oct. 23 and includes online learning, weekly live Zoom sessions and in-person workshops at three Vermont community composting sites. The fee is $50 for Vermonters ($150 for other students) and includes all materials. Visit go.uvm.edu/vtcompostingcourse to learn more and register. To request a disability-related accommodation to participate, email [email protected] or call 802-656-1777 by Aug. 28. Nonprofit resource. Common Good Vermont and Vermont Community Foundation announced the launch of Vermont Nonprofit HelpDesk, a new resource to connect Vermont's nonprofit organizations with support. Developed in partnership with the Nonprofit Legal Hub and CoLab, the HelpDesk addresses nonprofits' need to navigate complex legal, financial, operational challenges and find the right help when they need it. The HelpDesk is free to use. Any Vermont nonprofit can submit a question or request support through the contact form available at commongoodvt.org/helpdesk. A trained HelpDesk manager guides them to the right resource: a vetted online tool, a template, a training, or a trusted expert who can provide direct support. Do you have an item you would like to see in Community News? A milestone? A public announcement? A short news release about something entertaining going on in your town? Simply email the information to Times Argus at [email protected]. Be sure to put For Community News in the subject line. (Note: Times Argus do reserve the right to edit for length.) When submitting photographs, please be sure they are larger than 1MB in a jpg format.