Engineering Career Advancement Strategies

Should you try Google’s famous “20% time” experiment to encourage innovation? We tried this at Duolingo years ago. It didn’t work. It wasn’t enough time for people to start meaningful projects, and very few people took advantage of it because the framework was pretty vague. I knew there had to be other ways to drive innovation at the company. So, here are 3 other initiatives we’ve tried, what we’ve learned from each, and what we're going to try next. 💡 Innovation Awards: Annual recognition for those who move the needle with boundary-pushing projects. The upside: These awards make our commitment to innovation clear, and offer a well-deserved incentive to those who have done remarkable work. The downside: It’s given to individuals, but we want to incentivize team work. What’s more, it’s not necessarily a framework for coming up with the next big thing. 💻 Hackathon: This is a good framework, and lots of companies do it. Everyone (not just engineers) can take two days to collaborate on and present anything that excites them, as long as it advances our mission or addresses a key business need. The upside: Some of our biggest features grew out of hackathon projects, from the Duolingo English Test (born at our first hackathon in 2013) to our avatar builder. The downside: Other than the time/resource constraint, projects rarely align with our current priorities. The ones that take off hit the elusive combo of right time + a problem that no other team could tackle. 💥 Special Projects: Knowing that ideal equation, we started a new program for fostering innovation, playfully dubbed DARPA (Duolingo Advanced Research Project Agency). The idea: anyone can pitch an idea at any time. If they get consensus on it and if it’s not in the purview of another team, a cross-functional group is formed to bring the project to fruition. The most creative work tends to happen when a problem is not in the clear purview of a particular team; this program creates a path for bringing these kinds of interdisciplinary ideas to life. Our Duo and Lily mascot suits (featured often on our social accounts) came from this, as did our Duo plushie and the merch store. (And if this photo doesn't show why we needed to innovate for new suits, I don't know what will!) The biggest challenge: figuring out how to transition ownership of a successful project after the strike team’s work is done. 👀 What’s next? We’re working on a program that proactively identifies big picture, unassigned problems that we haven’t figured out yet and then incentivizes people to create proposals for solving them. How that will work is still to be determined, but we know there is a lot of fertile ground for it to take root. How does your company create an environment of creativity that encourages true innovation? I'm interested to hear what's worked for you, so please feel free to share in the comments! #duolingo #innovation #hackathon #creativity #bigideas

From IP basics to IP strategy 🌟 Scientists are key creators of intellectual property (IP). Therefore, it is important that they know about IP rights. It enables them to recognize patentable inventions, comply with IP policies, and make informed decisions about publishing and patenting. IP rights protect creations of the mind. The most common rights are: 💡 Patents: protect inventions, such as a genetically modified microorganism or a new drug. 🎨 Design rights: cover the appearance of products, like the look of a smartphone or the shape of a lamp. 🛡️ Trademarks: names and logos that distinguish a product from other products, e.g., the Google logo. 🔒 Trade secrets: confidential information that is kept secret, like a manufacturing process or chemical composition. 📚 Copyright: protects original works, including art and research articles 🌱 Plant breeder's rights: protect new plant varieties. Often, products aren't protected by a single IP right, but multiple. For instance, a biotech company may have: - Patents for technical aspects of a product, e.g., an improved version of CRISPR-Cas9. 🛡️ - Trademark for the product's name, e.g., HelixForge.™️ - Trade secrets for its manufacturing methods or the optimal buffer composition. 🔒 Such an IP strategy combines various IP rights, each protecting a different aspect of the product. This enhances product protection as it is harder for competitors to copy the product or create similar products legally. By aligning IP strategy with business objectives through marketing, further R&D, licensing and strategic partnerships, IP decisions become a cornerstone for building a long-term competitive advantage for a company. 🚀 Organizations of all types and sizes, from universities and startups to large corporations, use IP strategies. Check the examples below to see how various IP rights can synergistically protect a product.

The old approach of sending resumes and hoping for the best isn't working anymore. Thousands of talented engineers are competing for fewer positions. In this market, being skilled isn't enough. You need to be visible. The engineers who are landing roles fast aren't necessarily the most qualified. They're the ones who know how to promote themselves and stand out from the crowd. That's why I created this 5-𝘀𝘁𝗲𝗽 𝗮𝘁𝘁𝗿𝗮𝗰𝘁𝗶𝗼𝗻 𝘀𝘆𝘀𝘁𝗲𝗺 𝘁𝗼 𝗵𝗲𝗹𝗽 𝘆𝗼𝘂 𝗿𝗶𝘀𝗲 𝗮𝗯𝗼𝘃𝗲 𝘁𝗵𝗲 𝗻𝗼𝗶𝘀𝗲: 📍 Step 1: Optimize Your LinkedIn Profile ↳ Your headline should immediately showcase your specific expertise. ↳ Quantify your achievements. ↳ Make yourself discoverable when recruiters search. 📍 Step 2: Build a Killer GitHub Portfolio ↳ Create 3-4 production-grade projects with detailed READMEs. ↳ Show your thinking process. ↳ Prove your skills instead of just listing them. 📍 Step 3: Write Technical Content Document what you learn. ↳ Share project walkthroughs. ↳ Write about common mistakes. 📍 Step 4: Share Strategically Post your insights with context. ↳ Explain why topics matter. ↳ Document your learning journey consistently. 📍 Step 5: Grow Your Network ↳ Connect with recruiters proactively. ↳ Engage meaningfully with posts daily. ↳ Build relationships before you need them. The result: Instead of competing with hundreds of identical resumes, you become the engineer they already know and want to hire. This system works because it positions you as a known solution, not an unknown candidate. 📌 Want the complete breakdown with actionable tips? Download the full guide here: https://bit.ly/4mZk17A I really hope this is useful. Share this with someone in your network who could benefit from these strategies. 💬 What's the biggest challenge you're facing in this competitive market?

If you are starting an MS or PhD in biotech this Fall, here’s the advice I wish someone had given me on Day 1: The science will be hard—but the job market after might be harder. 1. Don’t wait until graduation to build your resume. Translate your skills into industry language each semester. For example: - Western blot → biomarker validation - qPCR → diagnostic assay development - Flow cytometry → cell therapy QC - Confocal microscopy → imaging biomarkers Collect bullet points the way you collect data. 2. Don’t just aim for technical knowledge. Learn to explain your work in terms of outcomes, timelines, and value-add. Practice explaining every project or experiment in simple language and be ready to answer: why does it matter? 3. Pay attention to where the funding flows—cell therapy, RNA, AI-biology. Fields shift quickly. Choose electives, side projects, and optional subjects with an eye on where investors are backing the future. 4. Make genuine friends with your classmates, peers, and professors. Think long-term. These relationships will help you find opportunities, discuss roles, and navigate life beyond the lab. 5. Get in the habit of writing. Careers grow when you can package ideas into papers, talks, or even LinkedIn posts. It could even start in a personal journal. Communication is leverage. Your degree will make you a scientist. You make yourself a professional. And through it all—have fun. These might just be the most formative years of your life :) For those who’ve already been through it: Feel free to add one piece of advice you wish someone had told you before grad school?

I spent 2.5 years in MIT's PhD program. My biggest takeaway: for most people, doing a PhD is a bad career move. The number one reason I see people going into PhDs is one few would admit: inertia. Education is like a train ride – you hop on at the elementary school station and continue the ride through to college and more. Hopping off the train isn’t easy, especially once you’re hardwired to think about success in grades, tests, and academic methods. Many people choose to stay in their comfortable seats and take the ride into a PhD program. When you ask them why, the answer is usually something like, “I wanted to stay in school” or "I didn't feel I was ready for industry." These are terrible reasons to do a PhD! A PhD isn’t school. During your program, you have to work (aka do your research) on things assigned to you by your manager (aka your advisor), and in exchange, you get a salary (aka your stipend). That’s a literal definition of a job. And a PhD is not just any job. It's a job specifically optimized for being a researcher and becoming a professor. If you’re 100% sure that’s what you want in life and have what it takes to get one of the highly competitive professorship spots, go for it! But in almost any other case, doing a PhD is a mistake. You should never make a PhD your “default” option. If you’re unsure about what to do, go to industry. And if you still feel strongly about doing a PhD after taking a chance in industry, go for it. The best PhD candidates I met at MIT and Harvard worked at firms like Tesla, Google, SpaceX, and McKinsey for 2-5 years before enrolling. They might be over 30 by the time they get their PhDs, but they figured out the industry wasn’t for them and fast-tracked to top-tier professorship positions. Arguably, that’s better than getting a PhD at 27 but ending up in a role that you would’ve qualified for without a PhD and without the years of industry experience to boot. I made a YouTube video addressing in more detail when you should or shouldn’t do a PhD called “Don't do a PhD | From a former MIT PhD” #phd #academia #education

She said yes to every single project. Yet, she was overlooked for the promotion. They said: “She’s irreplaceable.” “We’d be lost without her.” But when it came time to lead the next big thing - She wasn’t even on the list. Over the past decade working in women’s leadership, I’ve seen this story play out far too often. Women staying in roles long past their expiration. Not because they lack clarity - But because they’ve been conditioned to confuse loyalty with worth. Loyalty to a team. To a leader. To a company culture that praises their reliability... But never promotes their vision. So how do you ensure you’re valued - not just used - for all that you bring to the table? Here are 5 practical, research-backed strategies I’ve seen top performers consistently use: ✅ Be Known for Vision, Not Just Execution ↳ “She delivers” is solid. ↳ “She sets the direction” is strategic. ↳ Build a reputation rooted in foresight - not just follow-through. ✅ Document and Distill Your Wins ↳ Don’t wait to be noticed. ↳ Capture and communicate your impact consistently. ↳ Think: outcomes, initiatives, feedback snapshots. ↳ This becomes your proof of value during reviews, promotions, or pivots. ✅ Speak the Language of Business ↳ Translate your work into metrics that matter: revenue, retention, growth, efficiency. ↳ When leaders see your contribution tied to business outcomes, you shift from “nice to have” to “can’t afford to lose.” ✅ Build Cross-Functional Credibility ↳ Influence isn’t built in silos. ↳ Make your value visible across teams. ↳ When multiple departments rely on your insight, you become a strategic connector - not just a contributor. ✅ Create Strategic Allies, Not Just Mentors ↳ Power isn’t just about performance - it’s about proximity to influence. ↳ Nurture relationships with decision-makers, peer champions, and collaborators. Influence grows through meaningful connection. The truth is - being essential isn’t the same as being seen. You can be deeply loyal to others - and still loyal to your own growth. These shifts aren’t just career strategies. They’re acts of self-respect. Because when you decide to lead from alignment, not obligation - You stop waiting to be chosen. And start choosing yourself. 💬 Which of these strategies feels most relevant to where you are right now? I’d love to hear in the comments below. ♻ Repost if you believe it’s time to stop rewarding quiet loyalty - and start recognizing conscious leadership. 🔔 Follow me, Bhavna Toor, for more. 📩 DM me to bring our holistic leadership development programs to your organization - that are a powerful combination of inner-work and real-world strategy.

No, a high-quality research paper is not enough to create an impact with your work. (there are >3.5 million new science and engineering papers published yearly...) Throughout my academic journey, I've discovered that creating impact with your work isn't just about publishing papers but strategic positioning and intentional networking. Here are 5 critical pathways to impact that can also elevate your academic profile: Research Publication Strategy → Target relevant peer-reviewed journals → Collaborate across interdisciplinary domains → Develop a consistent publication track record Conference and Symposium Engagement → Present research at national and international conferences → Seek opportunities for panel discussions → Network with thought leaders in your field Digital Presence → Maintain an updated professional profile on platforms → Regularly share research insights on academic social networks → Create a comprehensive digital portfolio showcasing achievements Strategic Collaborative Research → Initiate cross-institutional research projects → Build meaningful partnerships with industry, academia, and policymakers → Contribute to multi-disciplinary research initiatives Professional Development → Pursue advanced certifications → Attend workshops and specialised training programs → Develop complementary skills beyond core research expertise Your academic journey is a continuous evolution. Embrace these strategies, and watch the impact of your work grow. #Research #Scientist #Science #Career #Professor #ChemicalEngineering #PhD Interested in diving deeper? Let's connect and discuss your growth trajectory!

➡️ What’s the best way to stick out as a scientist applying to roles at early-stage startups? ⬅️ Having been a hiring manager for >40 scientists into early-stage companies, it’s often your non-technical skills which are the deciding factor. This assumes you’re broadly a technical fit for the company in question (i.e. you have a PhD in cellular biology & have done a lot of cell culture or you have experience with drug or assay development). Why? Because early-stage means strategy will pivot. A scientist with broad expertise can be slotted into different teams. Flexibility is an asset in startup land. ➡️ So where do many scientists go wrong in the interview process? ⬅️ It’s in the non-technical skills, and specifically: ✅ Communication ✅ Commercialization awareness The challenge: A lot of scientists write these skills on their resumes. Not a lot of scientists do a good job of highlighting these skills in interviews. As a hiring manager, I am looking to get to confidence that if I send this newly hired scientist into a room of non-scientists, they’ll be able to concisely and accurately explain the decisions they’re making and why, in the context of the wider business. ➡️ Here’s how the best candidates have given me that confidence: ⬅️ Signals in the resume: ✅ 3 Minute Thesis ✅ Entrepreneurship pitch competitions/accelerator involvement ✅ Cross-functional collaborations (and not just with the chemistry or pharmacy departments. Think non-scientists!) Signals in the hiring process: ✅ Clear, concise answers to interview questions. ✅ Technical questions which intersect with business; think scale-up & distribution, Cost of Goods and Services (COGS), future product features. ✅ Deliberately considering the format of communicated responses. On that last point: Most scientists write narrative style responses to technical take-home challenges, which somewhat resemble academic papers. I’ve passed plenty of them through to the next stage on the basis of “this person has the technical capabilities to succeed.” However, a diagram, chart, or slide can show you not only have the technical depth of knowledge to succeed, but you also know how to position your knowledge in a way that’s easily digested by non-scientists. Now of course these skills can and will be improved on the job, but when I think about the highest performing scientists I've been lucky enough to hire over the years, most of them spiked in interviews in this area. Push-back or refinement welcome; I expect for bigger companies, where scientists have less interaction with non-technical functions of the business, this is less important 😊

I recently received a rejection from a journal. It was not just a rejection but a desk rejection—the kind where your manuscript does not even make it past the editor's desk. They mentioned that the work was not particularly novel and did not quite align with the journal. They had a point. I have been working on this material for a while, and perhaps the novelty become diluted in the process. Every scientist, at some point, faces rejection. It is a rite of passage in academia. Rejections happen all the time, and how we handle them matters. It is about resilience and recalibration. So, what can we do when faced with such setbacks? One way is to look for another journal. Sure, it is tempting to be discouraged, but the truth is, there are many journals out there, each competing for the best papers in their field. What might not be a good fit for one journal could be exactly what another is looking for. The key is knowing the landscape. So, take some time to research journals that are better aligned with your study’s focus, and give it another shot. Another important step is to revisit your literature survey. Journals often reject papers when they feel the work does not clearly state its contribution. We might think we have made a novel point, but it is easy to forget that novelty must be evident, not just to us but to reviewers who might not be familiar with the nuances of your research area. A strong, well-written literature review can be the bridge that takes your work from "not novel" to "groundbreaking." On data. Is your data presented in a way that highlights the core contributions of your work? It is easy to overlook the storytelling aspect of scientific research. Every figure, table, and graph should support the narrative of innovation. If you are not making your data sing, it is easy for reviewers to skim past your most important findings. Go back and ensure the way you present your data draws attention to the novelty. What, really, is novelty? It is a question every scientist grapples with at some point. Novelty is not just about being first; it is about doing something in a new way, solving a problem differently, or opening up a new avenue of research. It is the ability to see connections others do not. If we cannot articulate that innovation in a way that is compelling, the novelty is lost on others. Frame your research in a way that speaks to the current challenges in the field. Why is your work necessary? What questions does it answer that have not been addressed before? Handling rejection is part of the scientific process. Every rejection is an opportunity to refine your work and sharpen your message. Instead of dwelling on the "no," think of how you can make your next submission stronger. Every setback is a step toward making your research even better. So, embrace the process, learn from it, and let it guide you to eventual success. Good luck to everyone and especially to myself on the next submission!

Here are the 13 Tech Shifts you should include in your strategic planning. It’s again the time of the year for technology predictions. The new McKinsey & Company Technology Trends Outlook 2025 by Lareina Yee, Michael Chui, Roger Roberts, Sven Smit is here and it highlights 13 frontier technologies shaping the next decade. The common thread? AI isn’t just a trend: it’s the amplifier of everything. Let’s break it down: 🔹 AI Revolution (The Core Catalyst) 1. Artificial Intelligence: From diagnostics to discovery, AI is reshaping every industry. It’s becoming more multimodal, more capable, and more embedded. 2. Agentic AI: Think beyond chatbots: these are autonomous AI “coworkers” that plan and execute tasks independently, revolutionizing workflows in customer service, software dev, and even research. 🔹 Compute & Connectivity (The Infrastructure Enablers) 3. Application-Specific Semiconductors: Custom chips powering AI’s insatiable demand for speed, efficiency, and specialized compute. 4. Advanced Connectivity: 5G/6G, private networks, LEO satellites: unlocking edge intelligence, remote care, and real-time coordination. 5. Cloud and Edge Computing: Distributing workloads across cloud and edge to balance speed, sovereignty, and sustainability. 6. Immersive-Reality Technologies: From AR-assisted surgery to VR training in healthcare, immersive tech is going enterprise. 7. Digital Trust and Cybersecurity: AI needs trust to scale. Expect stronger identity, governance, explainability, and quantum-safe security. 8. Quantum Technologies: Still early, but breakthroughs are coming in drug discovery, encryption, and optimization. 🔹 Cutting-Edge Engineering (The Physical & Biological Frontiers) 9. Future of Robotics: Humanoids, cobots, and surgical robots working side by side with humans across industries. 10. Future of Mobility: Autonomous vehicles, delivery drones, and EVs reshaping how we move goods and people. 11. Future of Bioengineering: Personalized, engineered medicine and synthetic biology promise a leap in longevity and healthspan. 12. Future of Space Technologies: LEO constellations, space manufacturing, and global connectivity infrastructure. 13. Future of Energy and Sustainability Technologies: Clean energy systems, battery innovation, and carbon capture, all accelerating decarbonization. Why this matters especially in healthcare: We’re entering an era where AI doesn’t just support workflows, it takes over parts of them. From agentic AI in radiology to bioengineered therapies tailored to your genome, it’s already starting. My personal read into this: Innovation is no longer about adopting tech. It’s about integrating it responsibly, securely, and equitably. It‘s clear by now AI is the innovation you can’t ignore as it‘s the amplifier for everything! Your turn: Which of these 13 frontier trends excites, or worries you most?