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Is this also how you switch off during vacation?

Great collaborations make research enjoyable. Bad collaboration leaves people unhappy. 📍 In BAD collaborations: 1. The authorship list has the researchers with less contribution at the front while strong contributors are placed in the middle. 2. Concerns from collaborators are ignored by the main professor for the sake of ‘publishing the Big Finding’. 3. The professors / senior researchers in one team have radically different vision for the publication (e.g. one pushes for fast publishing while the other wants to get more statistics). 4. The leading PI is pushing hard but the collaborator is not interested and not ready to commit well. As a result, the study slows down and the students are in trouble. 5. One of the professors ‘trades’ their authorship (despite a big contribution) for something to ‘please’ the collaborator. This does happen sometimes. The students do not get their rightful authorship. 6. The collaboration is done for the sake of ‘publishing something’ (increasing the number of papers). (+ many more examples that you can write in the comments) 📍 The way I define a ‘GREAT collaboration’: - It makes everyone happier (everyone is heard, the word is truly joined) - It makes research go faster and deeper - It opens new research questions (e.g. for joint funding proposals) - It benefits everyone’s career (broadly defined) ❗️My message to all Young Professors: A great collaboration is a fulfilling & enjoyable experience. But the bad one can become super-stressful and even break your career. Be VERY careful with whom you collaborate. It’s easy to get ‘hooked’ on the collaboration that you don’t really need. ❗️For me, the collaborator should be: - As interested in the idea as I am - Expert in what he/she is contributing - Financially ‘well set’ and independent (low risk of ‘no more money’) - Easy to talk to and available for extensive discussions - Treating their students correctly and respecting my students Many think that collaborations are easy to do. But in fact - the great ones are really hard to find. #research #science #mechanicalengineering #chemicalengineering #chemistry

Yes, “how long the H-index is” does matter in academia. But for science, it does NOT. Big discoveries are often made by people with small metrics. Examples are: 1. Katalin Karikó got ONLY ~300 citations/year in 2005 when she discovered the potential use of mRNA in therapeutics. 2. Andre Geim had ONLY ~1500 citations/year in 2004 when his team discovered graphene. 3. Frances Arnold got ONLY ~200 citations/year in 1993 when she demonstrated the directed evolution of enzymes. (And many others) 📍 In academia: 1. Faculty positions are much easier to get when you have strong metrics after PhD+postdoc. 2. Funding is much easier to get when you you have big metrics. It’s the case for most countries. 3. Strong postdocs prefer to join groups where professors have big profiles. 📍 In science: 1. Big discoveries do not care about the journal. Publishing in Nature/Science does not turn the study into a discovery. 2. Big ideas do not care about funding. Most discoveries were made without millions of $$$ in allocated budgets. 3. Great talents full of ideas can be found at any place. You don’t need to go to “top university” to find them. ❗️My point is simple: Academia ≠ science. #PhD #research #science

How to deliver a great presentation? To deliver a great presentation, focus on these three key elements: Conciseness: Use fewer words and avoid bullet points. Pair photos and images for better memorability. Visual Aids: Include relevant visuals (e.g., pictures, charts) with large, readable text. Engagement: Share stories, interesting statistics, and brief videos to captivate your audience. Remember to rehearse extensively! 🎤👍

How would Einstein do research in 2024? Albert Einstein’s approach to ideation was unique and contributed significantly to his groundbreaking work. Let’s explore how he thought and what we can learn from his creative process. Combinatory Play: Einstein referred to his creative process as “combinatory play.” Instead of rigidly adhering to conventional thinking, he intentionally engaged in unrelated activities. This allowed his mind to wander freely and make unexpected connections. His famous quote, “I never came upon any of my discoveries through the process of rational thinking,” underscores the importance of divergent thinking and exploration. Avoid Overworking: Einstein believed that creativity was orthogonal to exhaustive work. In other words, pushing yourself too hard doesn’t necessarily lead to innovative ideas. To foster creativity, avoid overworking on a daily basis. Give your mind space to breathe and explore beyond the obvious. Zoom Out for Big Ideas: Instead of digging too deep into a specific problem, Einstein advised zooming out to see the big picture. Sometimes, stepping back allows you to identify novel solutions. Rest and reflection are essential for generating impactful ideas. Diverse Workspaces: Einstein emphasized the importance of diverse workspaces. For him, Stanford’s flourishing alleys provided inspiration during walks, rather than being confined to an office. Consider different environments—whether it’s a kitchen, gym, or outdoor space—to defocus from routine tasks and stimulate creativity. Enjoy Life While Creating: Defocusing doesn’t mean your brain stops thinking. You can enjoy life while your mind continues to make an impact. So, embrace “combinatory play,” take breaks, and explore various settings. Your best ideas might emerge when you least expect them. Remember, creativity thrives when we allow our minds to wander and connect seemingly unrelated dots. 🌟🧠✨. #research #science #phd #creativity

A student asked today if they could use emojis in a PhD thesis. The instinct answer came: Absolutely NOOO. Then she asked: WHY? Giving it some thought, we could not come up with an absolutely clear and rational reason. So eventually, gave a GREEN LIGHT. What is your position on this? What will a PhD thesis in 10-20-50 years look like?

Yann LeCun: “If you do research and don’t publish, it’s not Science. Research must be correct and reproducible.” Elon Musk: “Our mission of understanding the universe […] requires maximally rigorous pursuit of the truth, without regard to popularity or political correctness” 📍 However, even among scientists, “doing science” does not always equate to “doing genuine research.” Reproducibility Crisis: In fields like chemistry, medicine, biology, and physics, a significant portion of work remains irreproducible. The ability to replicate experiments and obtain consistent results is crucial for scientific progress. Awful Statistics: Some research suffers from poor statistical practices. Researchers may cherry-pick data or draw broad conclusions from a limited sample size. Methodological Expertise: Mistakes and misinterpretations often lurk in scientific publications. Even well-known scientists occasionally use methods without deep expertise in those areas. Asking Deep Questions: Many scientists stick to mainstream topics, avoiding riskier research. However, true breakthroughs come from asking novel and profound questions. 📍 My Point: Science is gaining public attention due to new technologies, discoveries, and social media. It’s crucial to maintain high-quality research: Be bold and explore uncharted territory. Publish rigorously and only when the study meets robust standards. Real science withstands the test of time, and you have the power to uphold its integrity. 🌟 Tamas Sohajda #science #research #education #publishing

In Science, All Outcomes Matter In the realm of scientific inquiry, every outcome holds significance. However, the landscape of research journals often paints a different picture: “No positive results? Apologies, but we exclusively publish highly impactful findings.” This prevailing attitude can hinder progress. Without sharing negative studies and data, researchers risk repeating futile work. The recent article in Nature eloquently highlights this issue. Solving the Problem New Journals, Conferences, and Formats for “Failed Experiments”Initiatives like the Journal of Trial & Error aim to expose the “ugly side of science”—the aspects of the process that have gone awry. Policy Changes Funders should mandate the public availability of negative outcomes. Regular journals should embrace descriptions of failed experiments, especially for impactful work. This transparency helps us understand limitations and challenges. Promotion committees should evaluate all outcomes from principal investigators (PIs). Open-Ended Papers Andrew Akbashev & Sergei Kalinin recently proposed a novel publishing format: open-ended papers. These can resemble Jupyter Notebooks or webpages. Researchers can document all results, describe outcomes, and continually add new findings as their study progresses. https://lnkd.in/duQ5tt6K The Data Dilemma Despite these solutions, much valuable data remains lost. Students fear project failure, while professors emphasize positive outcomes. The perceptual bias persists, even though science thrives on unbiased exploration. A Call for Change Let’s shift academic mentality. Failure signifies effort, and those who dare to explore risky avenues captivate me more than those who merely chase predictable outcomes. 🔗 Learn more about open-ended papers #science #research #publishing

Research means 99 out of 100 experiments will fail. Why should we embrace and respect failure in research? Embracing and respecting failure in research is essential for several reasons. How can failure be a valuable learning opportunity? 1. Alternative Approaches Importance: Failure forces researchers to explore fresh ideas and different approaches. Learning Opportunity: When one path fails, it opens the door to alternative methods or hypotheses. Case Study: Thomas Edison’s famous quote, “I have not failed. I’ve just found 10,000 ways that won’t work,” exemplifies this mindset. His relentless experimentation eventually led to the invention of the practical electric light bulb. 2. Persistence and Resilience Importance: Research is often a long-term and in-depth journey. Learning Opportunity: Failure builds persistence and resilience. Case Study: The development of innovations is crucial for firms’ survival and growth. CEOs and executives recognize innovation as a competitive necessity. Despite difficulties and failures, companies continue to invest in research and development (R&D) to foster innovation. 3. Quality Improvement Importance: Failure prompts critical analysis of findings and approaches. Learning Opportunity: Reviewing mistakes improves research quality. Case Study: In academia, where producing new knowledge is paramount, failure is an inevitable part of the research process. Learning from failures enhances subsequent research endeavors. 4. Entrepreneurial Success Importance: Entrepreneurs can learn from failures to succeed. Learning Opportunity: Failure becomes a stepping stone toward future accomplishments. Case Study: Many successful entrepreneurs faced setbacks before achieving breakthroughs. Their ability to learn from failures contributed to their ultimate triumphs. 5. Innovation and Adaptation Importance: Innovation requires adaptability and learning. Learning Opportunity: Failed innovations provide insights for future success. Case Study: Companies like Apple, Google, and Amazon have experienced product failures (e.g., Apple’s Newton, Google Glass). These failures led to course corrections and ultimately shaped their successful product lines. Remember, failure is not defeat; it’s a stepping stone toward progress. By embracing failure, researchers can refine their approaches, learn valuable lessons, and contribute to the advancement of knowledge. 🌟 If you’d like more examples or have specific questions, feel free to ask! 😊 Follow Tamas Sohajda and SciConn for more content around #research and #socialmedia #science #phd #communication

Do you use social media platforms to share your research findings or academic work? I really would like to better understand where we stand on this. I see many papers, patents, results getting published every day on both Linkedin and X, yet I am still not sure how general this is. Just a habit of a handful of people or a general tendency to rise? Please vote and repost to have a meaningful answer, thank you.