Careers

From Content Creators to Communication Partners: The Role of Motion in Scientific Storytelling

Posted on by Taylor McAda
Image generated by DALL-E.

Moving Science Forward — Literally

I’ve always believed that the best science stories don’t just inform — they move us. And in many cases, that’s quite literal.

Whether I’m designing a figure for a new assay or animating a step-by-step protocol, I see motion as a bridge that turns complexity into clarity. When used well, that bridge transforms scientific communication from dense and static into something dynamic, visual and memorable.

And it’s not just me — a graphic designer — saying this. Scholars like Daniel Liddle describe motion as a form of visual rhetoric: a way to persuade, clarify and build trust through movement. Motion isn’t just decoration — it’s meaning made visible.

In this post, I’ll explore why motion matters in scientific communication and how animation makes complex ideas easier to grasp. From turning a protocol into a story that sticks to making technical jargon something you can remember, motion design helps science feel more approachable and a lot more memorable.

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Non-Pharmacological Approaches to ADHD: Exploring Inflammation and Omega-3s

Posted on by Simon Moe

Attention-Deficit/Hyperactivity Disorder (ADHD) is a complex neurodevelopmental disorder that affects millions worldwide. Current therapeutic treatment relies on pharmaceutical approaches, but emerging research suggests that dietary supplements, such as omega-3 fatty acids, may offer complementary therapeutic options. A recent study published in the Journal of Psychiatric Research explores the relationship between inflammation and dietary supplements to determine how they might influence ADHD pathology. This work was conducted in Dr. Edna Grünblatt’s lab at the University of Zurich and was supported through Promega’s Academic Access Program. I had the chance to interview Dr. Natalie Walter, the lead author, to learn more about how her work offers potential opportunities for non-pharmacological interventions.

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Exploring Career Options for PhD Students: Planning for Success

Posted on by Lindsey Drake

Earning a PhD opens doors to a wide range of career opportunities across academia, industry, government, and beyond. While many students begin their PhD programs with specific career goals, research shows that career interests often evolve during their training (Brown et al., 2023). Therefore, exploring career options and remaining flexible to opportunities is important. By embracing career exploration and self-assessment, students can identify their best career options and make informed decisions about their next steps after graduation.

The Many Career Options for PhD Graduates

PhD graduates today find themselves in diverse roles, with opportunities extending beyond traditional academia. Career paths include:

  • Academia: Research-intensive faculty positions, teaching-focused roles, or administrative leadership.
  • Industry: Roles in biotechnology, data science, or consulting, often in research or management positions.
  • Government and Nonprofit Organizations: Research or policy roles in agencies such as the NIH (National Institutes of Health) and FDA (Food and Drug Administration), and others.
  • Additional Careers: Science communication, medical writing, marketing, patent law, or entrepreneurship.

During their training, PhD students develop highly transferable skills—critical thinking, project management, data analysis, communication, and problem-solving—that are highly valued across sectors (Sinche et al., 2017). Recognizing the value of these skills can expand career options for graduates.

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Third Annual Targeted Protein Degradation Symposium: Embracing the Excitement of Discovery

Posted on by Simon Moe

The third annual Targeted Protein Degradation (TPD) Symposium just wrapped up last month. It was kicked off with Poncho Meisenheimer, VP of Research and Development at Promega, likening the gathering of researchers to “kids in a biology candy store.” This playful analogy captured the vibrant energy and sense of exploration among the attendees, who convened to delve into the future possibilities of proximity-induced degradation. Poncho left attendees with three key questions to consider throughout the symposium:

  1. How can we focus on quantitative measures of cellular events in relevant models?
  2. How do we generate results that serve both human and AI models?
  3. How do we best embrace the excitement of discovery?

Nearly 150 participants from both industry and academia attended the two-day symposium. It was held on September 11th and 12th at Promega’s R&D hub, the Kornberg Center, in Madison, Wisconsin. The event, now in its third year, provided a familiar environment where collaborations flourished, and many attendees rekindled connections forged through previous interactions or partnerships in the field.

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iGEM Grant Winners Tackle Tough Problems in Synthetic Biology

Posted on by Anna Bennett
Conceptual image depicting dna strands intertwined with robotic parts.

In June, Promega proudly announced the ten winners of the 2024 Promega iGEM Grant. These extraordinary teams have been hard at work preparing for the iGEM Grand Jamboree, which will take place from October 23-26, 2024, in Paris, France. We interviewed a handful of this year’s grant recipients to learn more about their projects and journeys they’ve taken to reach this exciting milestone. Below are stories from four of the winning teams.

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The Casual Catalyst: Science Conversations and Cafes

Posted on by Michele Arduengo, PhD

There is no shortage of stories about great scientific collaborations that have taken root as the result of an excited conversation between two scientists over sandwiches and beer at a bar or a deli. One of the most famous examples of such a conversation was that between Herbert Boyer and Stanley Cohen when they attended a conference on bacterial plasmids in 1972—that very conversation led to the formation of the biotechnology field as the two scientists worked together to clone specific regions of DNA (1).  

“Over hot pastrami and corned beef sandwiches, Herbert Boyer and Stanley Cohen opened the door to genetic engineering and laid the foundations for gene therapy and the biotechnology industry.”  

Steven Johnson, author of Where Do Good Ideas Come From, credits the English coffee house as being crucial to the spread of the enlightenment movement in the 17th and 18th centuries (2). He argues that coffee houses provide a space where ideas can come together and form networks. In fact, he defines the concept of “idea” not as a single entity—a grand thought that poofs into existence upon hard work—but at its simplest level, a new idea is a new network of neurons firing in sync with each other.  

Johnson further argues that the development of great new ideas not only requires a space for ideas to bump into each other, connect and form a network, but also that great ideas are rarely the product of a single “Eureka” moment. Rather, they are slowly developing, churning hunches that have very long incubation periods (2).  

Science is Ripe with “Coffee House” Discoveries

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Expert Insights: A Look Forward at Multiplexing for in vivo Bioluminescence Imaging

Posted on by Simon Moe

Bioluminescent in vivo imaging tools

NanoLuc, NLuc

With advancements made over the past few decades, the future of in vivo bioluminescence imaging (BLI) continues to gain momentum. In vivo BLI provides a non-invasive way to image endogenous biological processes in whole animals. This provides an easier method to assess relevant systems and functions. Unlike fluorescent imaging, BLI relies on a combination of enzymes and substrates to produce light, greatly reducing background signal (Refaat et al., 2022). Traditional fluorescent tags are also quite large and may interfere with normal biological function. In vivo BLI research has been around for quite some time, primarily utilizing Firefly luciferase (Luc2/luciferin). A recent advancement was the creation of the small and bright NanoLuc® luciferase (NLuc). Promega offers an wide portfolio of NLuc products that provide ways to study genes, protein dynamics, and protein:protein interactions. To fully grasp the power of these tools, I interviewed several key investigators to determine their perspectives on the future of in vivo BLI. I was specifically interested in their thoughts on NLuc multiplexing potential with Firefly (FLuc), and future research areas. These two investigators are Dr. Thomas Kirkland, Sr. Scientific Investigator at Promega, and Dr. Laura Mezzanotte, Associate Professor at Erasmus MC.

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Will Artificial Intelligence (AI) Transform the Future of Life Science Research?

Posted on by Ken Doyle

Artificial intelligence (AI) is not a new technological development. The idea of intelligent machines has been popular for several centuries. The term “artificial intelligence” was coined by John McCarthy for a workshop at Dartmouth College in 1955 (1), and this workshop is considered the birthplace of AI research. Modern AI owes much of its existence to an earlier paper by Alan Turing (2), in which he proposed the famous Turing Test to determine whether a machine could exhibit intelligent behavior equivalent to—or indistinguishable from—that of a human.

The explosive growth in all things AI over the past few years has evoked strong reactions from the general public. At one end of the spectrum, some people fear AI and refuse to use it—even though they may have unwittingly been using a form of AI in their work for years. At the other extreme, advocates embrace all aspects of AI, regardless of potential ethical implications. Finding a middle ground is not always easy, but it’s the best path forward to take advantage of the improvements in efficiency that AI can bring, while still being cautious about widespread adoption. It’s worth noting that AI is a broad, general term that covers a wide range of technologies (see sidebar).

AI personified looking at a dna double helix against an abstract cosmic background
Image generated with Adobe Firefly v.2.

For life science researchers, AI has the potential to address many common challenges; a previous post on this blog discussed how AI can help develop a research proposal. AI can help with everyday tasks like literature searches, lab notebook management, and data analysis. It is already making strides on a larger scale in applications for lab automation, drug discovery and personalized medicine (reviewed in 3–5). Significant medical breakthroughs have resulted from AI-powered research, such as the discovery of novel antibiotic classes (6) and assessment of atherosclerotic plaques (7). A few examples of AI-driven tools and platforms covering various aspects of life science research are listed here.

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Can AI Help You Develop a Research Proposal?

Posted on by Jordan Nutting

Integrating artificial intelligence (AI) into the process of scientific research offers a wealth of efficiency-boosting tools that are transforming the ways scientists can approach their work. Many are already using AI to refine code, automate data processing, and edit papers, presentations, abstracts and more. Personally, I find generative language models like ChatGPT to be invaluable “editorial assistants” in my work as a science writer, helping me work through wonky sentence structures, be more concise and get over writer’s block, to name a few applications.

An AI-generated image of a man in a white lab coat who has a thoughtful look on his face. He is looking off camera with his hand on his chin. The background is a field of light bursts and bright lines against a dark backdrop.
Image generated using Adobe Firefly

But a scientist’s work doesn’t only involve writing or analyzing data, making presentations or keeping up with the literature. An essential component of any research scientist’s skillset is their ability to develop entirely new ideas and novel research proposals. Coming up with research questions and plans is a central component of graduate education and research careers, both in academia and industry.

As AI continues to advance and find broader use, a critical question arises: Can AI play a pivotal role in the creative process of developing entirely new ideas, such as crafting novel research proposals?

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The R&D Flex Team: A Unique Research Scientist Opportunity

Posted on by Jordan Villanueva

Sarah Mahan embraces change. In fact, she doesn’t just embrace it, she seeks it out, running towards change with arms wide open. 

“If I could do a different thing every week, I would. That’s what my job would be.”

Sarah made her dream a reality when she began leading the Promega R&D Flex Team. This group of diverse research scientists moves around Kornberg Center, contributing resources to accelerate the development of technologies like Lumit Immunoassays and PowerPlex chemistry. They don’t specialize in any field or technology, but rather are constantly challenged to learn new skills quickly. Everywhere they go, they help R&D teams generate more data, answer more questions, and deliver results in less time.

“In short,” Sarah says, “we’re helping research teams make better products, faster.”

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