Scientist, Translational Computational Biology (all levels)

As a Scientist in Translational Computational Biology at Precede Biosciences, you'll blend biological insights with computational techniques to create predictive models crucial for clinical applications. Your role includes leading projects that connect biological understanding to computational analyses, refining epigenomic data's clinical impact, and developing novel predictors for diagnostic use. You'll also collaborate with cross-functional teams to transform innovative diagnostics into reality.

Qualifications for the Scientist position at Precede Biosciences include experience in computational analyses of the epigenome and the ability to present findings effectively. While we're open to all experience levels, familiarity with programming in R (Bioconductor) or Python is essential. We also value individuals who are eager to contribute in a fast-paced startup environment and possess a collaborative mindset.

Our culture at Precede Biosciences is built on purpose, teamwork, and excellence. We focus on nurturing a strong team spirit while encouraging individual initiative and accountability. As a Scientist, you’ll find an environment that values diversity and promotes learning from various perspectives. You’ll have the freedom to take on new challenges while receiving feedback to promote both personal and team-driven growth.

At Precede Biosciences, a Scientist can expect to work on innovative projects that bridge the gap between biological understanding and computational analysis in diagnostic applications. You’ll lead analyses of novel epigenomic data, explore the biological underpinnings of various diseases, and collaborate with a diverse team to deliver impactful solutions that advance diagnostics—paving the way for significant patient outcomes.

Absolutely! Experience in startup culture is highly beneficial for the Scientist role at Precede Biosciences. The fast-paced environment requires adaptability, self-direction, and a proactive approach to problem-solving. Candidates who thrive in such settings and are excited by the challenge of developing innovative solutions in a collaborative atmosphere will find Precede a perfect match.

In answering this question, highlight your experience in analyzing biological data and how you translate that into computational models. Provide examples of past projects where you've successfully combined these elements and discuss any specific methodologies or tools you employed in the process.

Discuss your proficiency in R (Bioconductor) or Python, providing specifics about projects where you utilized these languages for computational analysis. Share examples that demonstrate your capability to manipulate data and derive insights relevant to biological questions.

Select a specific challenge from your experience and explain the context, the steps you took to tackle the issue, and the outcome. Focus on highlighting your problem-solving skills and your ability to remain resilient in a fast-paced environment.

Discuss the biological factors essential to your modeling process like epigenetic markers or disease-relevant systems. Emphasize your understanding of how these factors influence disease and how you incorporate this knowledge into your predictive analyses.

Talk about your approach to validating your computational analyses through collaboration with clinical teams or by integrating feedback from stakeholders. Mention how you strive to create clinically applicable predictive models and the importance of real-world data in this process.

Share your methods for staying informed and engaged with the field, such as attending conferences, reading relevant journals, or participating in online forums. Highlight any recent research or breakthroughs that have inspired your work.

Demonstrate your ability to simplify complex concepts by providing an example where you successfully communicated your findings to a non-technical team. Emphasize your communication skills and the strategies you used to make the data relatable.

Discuss your approach to collaboration, emphasizing communication, understanding different perspectives, and working towards common goals. Provide an example where you engaged with diverse team members to achieve a successful project outcome.

Reflect on your passion for merging biology with data science and how it drives your commitment to improving patient outcomes. Share what aspects of computational biology excite you the most and why you are passionate about making impactful contributions.

Identify a key skill, such as analytical thinking or data interpretation, and explain why it’s vital in this role. Provide examples of how you’ve developed this skill and applied it to achieve successful outcomes in your previous work.