Sr. Scientist, Computational Biology

Altos Labs; Cambridge; Hybrid; GBP 50,000 - 90,000; Full time

Job summary

Join an innovative firm at the forefront of scientific research, where you will contribute to groundbreaking AI initiatives in computational biology. This role involves collaborating with a diverse team of experts to model cellular processes and develop predictive algorithms that can lead to transformative treatments. You will work in a dynamic environment, utilizing state-of-the-art AI tools and methodologies to analyze complex biological data. If you are passionate about scientific discovery and eager to make a significant impact on human health, this is the perfect opportunity for you to thrive and grow.

Qualifications

• PhD in a relevant field with strong emphasis in biological modeling.
• Expertise in AI methods for biological design and dynamical systems.

Responsibilities

• Modeling and analysis of biological processes through software development.
• Collaborate with scientists to enhance biological knowledge discovery.

Skills

AI methods

Mathematical modeling

Dynamical systems

Cell biology

Machine learning

Statistical methods

Data-driven modeling

Education

PhD in Biology

PhD in Computational Biology

PhD in Computer Science

Tools

Python

C

R

GitHub

Docker

Pytorch

NVIDIA CUDA

Job description

Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life.

Diversity at Altos

We believe that diverse perspectives are foundational to scientific innovation and inquiry. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know that they are valued for their unique perspectives. We are all accountable for sustaining a diverse and inclusive environment.

What You Will Contribute To Altos

The Altos Labs Institute of Computation (IoC) is seeking an independent and highly motivated Computational Biology Scientist to build, maintain, and support our hybrid AI initiative to model cellular processes.

The position will work in a multi-disciplinary research environment to assist investigators in algorithm development and implementation, and will work across the software development life cycle, including software design, coding, testing, deployment, and maintenance. The ideal candidate will be a good communicator and have a growth mindset with an enthusiasm for scientific discovery and strong interest in applying a combination of AI methods and mathematical models toward understanding mechanistic aspects of cellular processes with all experimental labs at Altos Labs.

The ideal candidate is particularly interested in multi-scale (systems) biochemistry and molecular biology of reprogramming, a dynamic field that seeks to understand complex biological systems by integrating data about biochemical components and help design interventions that direct cellular states along desired trajectories. This includes working with quantitative “big data” and building predictive models to develop novel theories. Our ultimate goal is to contribute to improving human lives through better-informed treatments.

Responsibilities:

• Contribute to modeling, simulation, and analysis of mechanistic or data-driven models of biological processes through software development in a highly collaborative environment. This will include:
• Exploring and developing ML algorithms to solve complex problems and draw conclusions.
• Apply state of the art AI tools to infer and model cellular dynamics from large data sets.
• Applying strong coding experience to model development using existing languages(s) and framework(s).
• Using AI as a tool to answer a scientific question, involved in the research and development aspects.
• Design and implement pipelines to mechanistically model cellular processes from model instantiation to simulation, calibration, and analysis.
• Collaborate with other scientists to characterize model behaviors, predictions, refinements, and accelerate the biological knowledge discovery.
• Developing research programs on partial cellular reprogramming, with the intent of closing the feedback loop between experimental and theoretical work, at multiple scales, from molecules to cells, tissues and even whole organisms.
• Working at the interface between mathematical and computational models, and AI methods, with the aim of establishing design principles of rejuvenated cells.
• Collaborating with both experimental and computational scientists across Altos.
• Influence best practices in areas such as Bayesian optimization, causal inference, building and assessing predictive models, analyzing biological networks, and analysis and visualization of -omics data.
• Maintain documentation and keep up-to-date as needed.
• Contribute to software releases (e.g. via GitHub, PyPI, Anaconda, Docker Hub).

Who You Are

The ideal candidate will be a strong collaborator with a background in dynamical systems and mathematical modeling of biological systems. Be able to demonstrate significant AI experience/application in conjunction with a working understanding of cell biology and/or biophysics. The level of the position will depend on the qualifications of the selected candidate.

Minimum Qualifications

• PhD in Biology, Computational Biology, Computer Science, or closely related field with strong emphasis in biological modeling.
• Relevant industry and/or academic experience.
• Expertise and a track record of using methods from artificial intelligence for biological design.
• Record of applications of dynamical systems to problems of synthetic biology.
• Record of applications of data driven modeling methods and AI to synthetic biology.
• Demonstrable experience of developing new statistical and machine learning-based methods for analyzing biological data to produce biological insights about cell health and rejuvenation.
• Experience working with mechanistic models (PDE/ODE, SDE, dynamical systems).
• Experience working with state of the art ML tools (transformers, GNN, etc.).
• Experience working with hybrid AI models (e.g., SINDy).
• Working knowledge of cell biology.
• Experience with Python, C, R or related scientific computing languages.

Preferred Qualifications

• Experience working with causal representation learning.
• Experience with RAG (retrieval-augmented generation) and GraphRAG a big plus.
• Experience with building and deploying software on GitHub, PyPI, Anaconda Cloud, and Docker Hub, as well as use of Pytorch lightning, Git, test-driven design.
• Knowledge of parallel computing technologies, such as NVIDIA’s CUDA platform, OpenCL, and OpenMPI.

The salary range for Cambridge, UK:

Exact compensation may vary based on skills, experience, and location.

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What We Want You To Know

We are a culture of collaboration and scientific excellence, and we believe in the values of inclusion and belonging to inspire innovation.

Altos Labs provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

Altos currently requires all employees to be fully vaccinated against COVID-19, subject to legally required exemptions (e.g., due to a medical condition or sincerely-held religious belief).

Thank you for your interest in Altos Labs where we strive for a culture of scientific excellence, learning, and belonging.