Computational Scientist, Neuroscience

As a Computational Scientist at Altos Labs, your main responsibilities will include building and managing omics analysis pipelines and machine learning workflows. You'll conduct studies to optimize therapeutic targets aimed at brain rejuvenation and work closely with scientists from various disciplines. Your role will also involve bridging communication between experimental teams and software development, ensuring the smooth operation of systems in a cloud environment.

To qualify for the Computational Scientist position at Altos Labs, you will need a PhD in Neuroscience, Computer Science, Biomedical Engineering, or a related field. Additionally, you should have experience with programming languages like Python, C++, or Scala, along with previous experience in handling omics data and applying software engineering practices in scientific environments.

At Altos Labs, diversity and inclusion are at the heart of our operations. We believe that a diverse team is essential for innovation and scientific inquiry. Altos ensures that all employees feel valued and included by promoting a culture of belonging and accountability, encouraging a variety of perspectives in all aspects of our mission.

Computational Scientists at Altos Labs have multiple pathways for career advancement, depending on qualifications and experience. Positions range from Scientist I to Senior Scientist II, each with increasing responsibilities and roles in leadership, project management, and innovation in brain rejuvenation research.

Altos Labs is dedicated to restoring cell health and resilience through groundbreaking cell rejuvenation approaches. As a Computational Scientist, your work directly contributes to this mission by analyzing large datasets, identifying therapeutic targets, and applying machine learning techniques, all of which are vital for advancing our understanding of brain aging and developing effective interventions.

In your response, focus on specific projects where you successfully managed large datasets, detailing the tools and technologies employed. Highlight your understanding of machine learning algorithms and frameworks, and how you utilized these skills to solve real-world problems.

Discuss your approach to collaboration by emphasizing your ability to communicate complex concepts clearly. Provide examples of how you’ve worked with scientists from different disciplines to bridge gaps in understanding and drive projects forward.

Share your strongest programming languages and offer specific examples of projects where you applied them. Discuss how these languages were instrumental in solving technical challenges related to data analysis or machine learning.

Detail a specific project that posed challenges, whether technical, logistical, or team-related. Emphasize your problem-solving abilities and how you leveraged teamwork to find solutions and achieve the project’s goals.

In your response, discuss your methodologies for data validation, error checking, and reproducibility. Highlight any best practices you've developed or followed to maintain high standards for data integrity.

Explain your strategies for translating technical jargon into accessible language. Provide examples where you successfully communicated complex ideas to non-technical audiences, ensuring everyone is aligned and informed.

Talk about your commitment to continuous learning. Mention relevant journals, conferences, and online courses you engage with, as well as any professional networks you belong to that help you stay informed about industry trends.

Discuss tools or methods you've used for project management and prioritization. Share an example where your organizational skills allowed you to successfully manage multiple responsibilities without compromising quality.

Reflect on the values and mission of Altos Labs. Explain how the focus on restoring cell health and the collaborative culture resonates with your professional aspirations and personal goals, making it an exciting opportunity for you.

Articulate how your academic qualifications and experiences in neuroscience or related fields equip you with a unique perspective when developing computational solutions. Discuss specific insights or skills that enhance your capability to contribute effectively to the role.