Madlen Wilmes, co-author of 'Computing Skills for Biologists,' shares her insights on essential computing skills for biologists. She discusses her transition from academia to finance, highlighting how transferable data analysis skills can open unexpected career paths. Madlen emphasizes the importance of programming languages like R and Python in data science. She also covers the challenges and advantages of moving into industry, including the need for strong networking and collaboration skills, while addressing the impact of soft skills on professional success.
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Quick takeaways
The book 'Computing Skills for Biologists' provides practical tutorials on essential computing skills for enhancing data management in scientific research.
The transition from academia to industry highlights the value of transferable analytical skills and the importance of soft skills like teamwork in career advancement.
Deep dives
The Value of Computing Skills for Scientists
Computing Skills for Biologists is highlighted as an essential resource for both biologists and natural scientists seeking to enhance their data analysis capabilities. The book is structured like a cookbook, offering practical tutorials on computing skills, particularly focusing on Unix and shell scripting, which can greatly streamline data management tasks in research. Students and professors can utilize the book either for self-directed learning or as a teaching resource, making it versatile for various academic settings. The companion website further supports learning by providing additional materials and resources to aid in the application of these skills.
Transitioning from Academia to Industry
The podcast discusses the journey of a biologist who transitioned into the finance sector, illustrating the transferability of skills between academia and industry. Although initially hesitant about leaving a research-oriented career, the individual leveraged analytical and data management skills acquired in academia to find opportunities in finance. This transition underscores the value of computational skills, critical thinking, and effective communication in diverse job markets. Through personal anecdotes, the discussion emphasizes that a background in science can lead to success in jobs that may not explicitly title themselves as 'data analyst.'
Foundational Goals in Scientific Computing
The book defines key philosophies that support effective scientific computing, including automation, reproducibility, and simplicity. These principles serve as guiding frameworks that can enhance scientific research across various disciplines. Even though many learners may find coding challenging, the book aims to bridge that gap by providing structured learning paths for novices. The author stresses that grounded knowledge in coding practices, such as version control and proper documentation, are vital for producing reliable and reproducible research outcomes.
Building Collaborative Skills in Industry
A significant focus of the conversation is the importance of soft skills in professional environments, particularly the collaborative dynamics in industry versus academia. The narrative emphasizes the necessity of teamwork and interpersonal skills for success in a corporate setting, contrasting this with the often solitary nature of academic research. The speaker reflects on the learning experiences in previous jobs that underscored how vital fostering relationships and understanding workplace culture is for navigating industry challenges. This underscores the notion that while technical skills are crucial, the ability to collaborate effectively can be just as important for career advancement.
This season it’s become clear that computing skills are vital for working in the natural sciences. In this episode, we were fortunate to speak with Madlen Wilmes, co-author of the book "Computing Skills for Biologists: A Toolbox". We discussed the book and why it’s a great resource for students and teachers. In addition to the book, Madlen shared her experience and advice on transitioning from academia to an industry career and how data analytic skills transfer to jobs that your professionals might not always consider. Join us and learn more about the book and careers using transferable skills.
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