Computational Scientist, Multiscale Modeling

What You Will Contribute To Altos

About modeling at Altos:

At Altos we are focused on understanding the origins of cellular loss of resilience as part of diseases and aging and develop strategies to restore cellular health. We believe that a diverse, highly collaborative environment will give us the best chance to achieve these goals. 

About the Work Unit:

The Multiscale Modeling Group works closely with the other members of the Computational Biology Hub and collaborates with experimental units toward understanding mechanistic aspects of cellular processes. The group is interested in understanding the mechanisms governing partial cellular reprogramming at multiple scales, with the aim of designing novel interventions. We use a combination of big-data analysis, mathematical models, AI/ML, and advanced computational methods to understand how biomolecular interactions process cellular signals and lead to emergent behaviors across scales from cellular to tissue levels. We collaborate strongly with experimental groups to ensure our models explain observed data and propose actionable hypotheses. 

Responsibilities

Key Functions:

• Drive projects that employ molecular modeling, coarse grain modeling, simulation, and analysis of bio molecular interactions involved in key biological processes, through software development and applications in a highly collaborative environment. 
• Integrate molecular modeling with pipelines to develop small molecule or small protein modulators, integrate results with models of cellular processes, and in particular aid with parameter inference, model calibration, and analysis. 
• Collaborate with other scientists to understand protein-protein interactions and protein-small molecule interactions that will modulate cellular behaviors. Formulate predictions to guide experiments, predict potential outcomes, refine existing knowledge, to accelerate discovery.
• Influence best practices in areas such as free energy calculations, use of AI in molecular modeling, coarse grained modeling, multiscale modeling, Bayesian inference, building and assessing predictive models, analysis and visualization of structural data.
• Maintain documentation and keep up-to-date as needed.
• Contribute to software releases (e.g. via GitHub, PyPI, Anaconda, Docker Hub).
• Contribute to project management. 

Who You Are 

Minimum Qualifications

Qualifications:

• PhD in Systems Biology, Biophysics, Bioinformatics, Bioinformatics related field with strong emphasis in molecular modeling.
• Solid grounding in statistical mechanics, statistical physics, or related disciplines and familiarity with modern applications of statistical mechanics methods for molecular modeling.
• Experience with Machine Learning / AI techniques used for molecular modeling to accelerate molecular simulations and infer structural features using high-performance computing environments.  
• Familiarity with molecular modeling tools such as OpenMM, DeepDriveMD, Alphafold, etc., and their use in molecular modeling. 
• Familiarity with coarse grained and mesoscale modeling methodologies to explore biochemical interactions across multiple scales. 
• Familiarity with mammalian biochemistry, molecular biology, and cell biology. 
• Strong programming skills with Python, C, Julia or related scientific computing languages coupled with a sound understanding of object-oriented programming.
• Ability to work independently, troubleshoot problems, and propose solutions alongside working tightly with a team of complementary scientists. 
• Strong problem-solving skills and collaboration skills coupled with rigorous, creative thinking.

Experience and Skills:

• In-depth knowledge of one or several of the following areas: Molecular dynamics, free energy calculations, force field development, AI methodologies for molecular modeling, structural biology analysis, integration of experimental data in computer modeling.
• Proficiency in various computational techniques such as molecular dynamics, free energy calculations, docking, and homology modeling.
• Proven publication record in the general area of computational chemistry, molecular biology and systems biology. 
• Strong written and oral communication skills, with experience presenting and communicating research work. 
• Ability to work in a team setting or independently as needed to contribute to ongoing projects.
• Experience building and deploying software on GitHub, PyPI, Anaconda Cloud, and Docker Hub.
• Experience with high-performance computing environments such as AWS, Microsoft Azure, ACCESS, INCITE environments.   
• Knowledge of parallel computing technologies, such as NVIDIA’s CUDA platform, OpenCL, and OpenMPI. 

Preferred Qualifications:

• Hands-on experience with molecular simulation platforms such as OpenMM is strongly preferred. 
• Hands-on experience with AI approaches for molecular simulations such as DeepDriveMD is strongly preferred. 
• Hands-on experience with development and application of free energy methods and using them for protein-protein interactions and peptide / small molecule design strongly preferred. 

The salary range for Redwood City, CA:

• Computational Scientist I : $141,950 - $192,050
• Computational Scientist II: $167,000 - $242,400
• Senior Computational Scientist I: $202,000 - $270,000

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

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