Cross-Disciplinary Skill Development

The Communication Skills That Actually Accelerate Bioinformatics Careers Technical excellence gets you in the door. Communication skills get you promoted. I have been watching this pattern for years now. The bioinformaticians who advance fastest are not necessarily the most brilliant programmers or the deepest domain experts. They are the ones who can translate complex computational insights into language that biologists, clinicians, and business stakeholders actually understand. Modern bioinformatics requires constant collaboration with biologists, computer scientists, statisticians, and healthcare professionals. Field professionals must be able to collaborate effectively with biologists, computer scientists, statisticians, and healthcare professionals. It requires technical skills and strong communication abilities to ensure that ideas and findings are clearly understood across disciplines. What I find interesting is that this skill becomes more valuable as AI tools democratize technical knowledge. (Almost) anyone can run a (basic) genomic analysis pipeline now. But explaining why that analysis matters, what the limitations are, and how the results should influence clinical decisions - that requires human judgment and communication skills that AI cannot replicate. So try to position yourself as "bioinformatics translator" who can bridge the gap between computational insights and biological questions. Employers seek professionals who can navigate high-performance computing systems or cloud platforms like AWS and bridge communication gaps between biology and IT teams. They are not just generating results - they are making those results actionable for their colleagues. This shows up in unexpected ways. The ability to write clear documentation becomes a competitive advantage when your pipelines need to be used by other team members. Being able to explain abstract concepts in simple terms makes you invaluable in cross-functional meetings. Knowing how to present data visualizations that tell a story rather than just displaying numbers sets you apart from peers who focus purely on technical implementation. Companies are desperate for people who can combine biological knowledge with engineering discipline, but they are equally desperate for people who can communicate that combination effectively to diverse stakeholders. The technical skills get you qualified for the role. The communication skills determine how far you go in it. In a field where interdisciplinary collaboration is essential, the professionals who master both the science and the storytelling are the ones building careers that scale. #Bioinformatics #CareerDevelopment #Communication #InterdisciplinarySkills #ProfessionalGrowth

Think about the last project you worked on. Did it really need just one skill? Or did you have to connect different pieces together? Early in my career, I thought going deep in a single skill would guarantee long-term success. It worked… for a while. But the world shifted. Tech stacks evolved. Roles blurred. Problems no longer fit neatly into one box. Today’s challenges demand cross-domain thinking. The following two arrows define your career growth: - Vertical → Depth: Mastery in one area. - Horizontal → Breadth: Awareness across disciplines. That’s why the T-shaped skill set became the gold standard: - One deep area of mastery. - Broad awareness around it. But the industry is shifting again. Enter the comb-shaped professional. Multiple deep verticals.  Still broad.  Even more versatile and adaptable. Picture a backend engineer who also knows AWS, DevOps, and system design. Or a frontend engineer who’s equally strong in accessibility, performance, and UX. When projects change, they adapt. When new challenges arise, they step in. When opportunities appear, they’re ready. Depth earns trust. Breadth earns opportunity. Build both.

With disruption accelerating across industries, many believe that greater specialization will be key to professional success—“learn X to get Y.” But is that enough? While deep expertise is valuable, breadth and adaptability are just as critical. In uncertain environments, companies need talent who can connect the dots, synthesize new information, and pivot quickly—not just at the leadership level, but across the entire organization. These reflections brought me back to David Epstein’s Range, which I recently revisited and thoroughly enjoyed. His book makes a compelling case for how diverse experiences and cross-disciplinary thinking help individuals navigate uncertainty and drive innovation in a variety of domains - from sports and music to science and beyond. This is something we see firsthand at IESE Business School. The most effective professionals aren’t just specialists—they are strategic thinkers with a broad perspective. A general management approach equips them to break silos, adapt across industries, and make high-impact decisions. That’s why we emphasize a holistic, general management perspective that encourages business leaders to think beyond functional expertise and consider the broader impact of their decisions. As industries transform, the companies that thrive are those with teams who see the bigger picture, embrace diverse experiences, and navigate complexity with confidence.

Inbox Q&A: What advice would you give to a graduate student or post doc who is interested in startups/industry research? I get this one a LOT. During my PhD, “industry research” seemed like a good fit. I gravitated towards translational research projects and I was motivated by outcomes which felt like they could tangibly improve the world - even for one individual. Just one problem: I had no exposure to the world of startups or industry. I didn’t know what skills I should be developing during my PhD training - really, the ideal time to focus on your career development and education! Here’s what I should have been doing as an early career scientist interested in startups/industry research: ➡️ Learn advanced statistics Why? Design of Experiment (DoE) strategies allow you to test many experimental factors in one simplified experiment. More knowledge, for less time & money. Super valuable in industry (and I’d argue should be used MUCH more often in academic research). Here’s how: Courses & free trials of DoE softwares can be found on the internet. ➡️ Practice communicating science to generalists Here’s how: Three minute thesis conference, telling non-scientists about what you’re working on & why they should care Basic? Sure. But with more practice you’re more likely to clearly communicate with, impress, and ultimately work well with the non-scientists interviewing you. ➡️ Meet & learn from entrepreneurs. Why? In startup world, “cross disciplinary collaboration” means working with the product, sales, and operations teams - not the chemistry lab across campus like I thought! Understand entrepreneurs so you’ll understand your future employer’s executives. Plus you never know when one of them might be hiring or know someone who is 😉 Here’s how: Start with your university’s startup hub, then try external incubator/startup community events or online networking. ➡️ Practice “project management” Why? You’re already “project managing” a research study. Most startups do this with formalised systems - kanban boards, ghantt charts, and regular critical path analysis to ensure science progresses efficiently. Here’s how: Download a basic project management tool and get comfortable tracking your science. Adopting the mindset of “doing science super efficiently” takes time and who knows? Maybe you’ll shave a few months off of your PhD research 😉 I currently use Notion - a basic kanban board will work well for most academic research projects - but JIRA, shortcut, atlas, and monday.com may be more aligned to what your future startup lab is using (especially if you collaborate with engineers). --- The good news: I didn’t do any of these and I still got a job at a pre-seed startup which grew very quickly, forcing me to gain all of these skills and more. But our sector’s market is tougher now, so these are just a few of the areas I’d suggest you think about - beyond your science, of course!

The old playbook for leadership is crumbling.  Leading in the new world of work, means constantly reinventing yourselves. Technology is reshaping how we work faster than ever before. Artificial intelligence, automation, and digital platforms are making traditional career paths disappear. Companies need leaders who can navigate uncertainty, embrace change, and turn disruption into opportunity. The most successful leaders won't be those with the most experience, but those with the greatest ability to learn and adapt. What does it take to be a Future-Fit Leader? Here's an excerpt of concepts from my book: REINVENT 4.0: 8 Traits to Help Leaders Lead Better 1️⃣ Risk-taking Mindset ↳ When AI handles routine tasks, leaders must explore new ground. ↳Brave leaders dare to go where computers can't predict. 2️⃣ Entrepreneurial Thinking ↳AI processes information; humans create meaning. ↳Spotting opportunities is about seeing potential others miss. 3️⃣ Inclusiveness ↳Diverse views prevent AI bias. ↳Real innovation comes from understanding different human experiences. 4️⃣ Noticeable ↳Your human skills are your true power. ↳Where machines calculate, humans inspire and solve creatively. 5️⃣ Vulnerability ↳Trust isn't built by data, but by genuine human connection. ↳Being real matters more than being perfect. 6️⃣ Empathy ↳Feeling and understanding human emotions is something machines can't learn.    ↳ Emotional intelligence is a leader's secret weapon. 7️⃣ Networking ↳ Real connections matter more than digital links. ↳ Strong human relationships drive true innovation. 8️⃣ Trans-disciplinary Learning ↳ Breaking traditional boundaries creates new insights. ↳ Great leaders connect dots across different fields of knowledge. In the age of rapid transformation, your capacity to reinvent yourself is your most valuable leadership skill. ♻️ Share this to help others to be future ready ☎️ Let's have a conversation on how I can help you be ready to lead in the future. Follow Adeline Tiah 謝善嫻 for more content on leadership culture, reinvention and future of work.

The Surprising Benefits of Cross-Industry Learning 🌐 Have you ever found inspiration in the most unexpected places? I have—and it’s changed how I approach my work. Some of my best ideas didn’t come from marketing textbooks or strategy sessions. Instead, they came from looking outside my industry entirely. Why Cross-Industry Learning Matters 💡 Here’s why stepping outside your professional bubble is worth it: 💪 Fresh Perspectives: Looking at a challenge through the lens of another industry can spark creative solutions. 💡 Innovative Ideas: Borrowing strategies from different fields often leads to unique, impactful approaches. 🚀 Broader Skill Set: Gaining insights from other industries sharpens your adaptability and resourcefulness. A Personal Example 🤔 I once took inspiration from the hospitality industry. Hotels excel at anticipating guest needs, often providing exceptional service before it’s even requested. I adapted that mindset to customer outreach for a digital campaign, focusing on pre-emptive solutions for client pain points. By proactively offering value instead of waiting for requests, we saw a noticeable boost in engagement rate and campaign success. It was a simple shift in thinking, but it made all the difference. Cross-industry learning isn’t just about gathering ideas—it’s about reshaping your perspective to approach challenges creatively. What’s an idea you’ve borrowed from another industry that changed the way you work? Let’s swap stories in the comments! 👇 #CrossIndustryLearning #Innovation #ProfessionalDevelopment #GrowthMindset #LinkedInTips #digitalmarketing