Computational Biologist

Company Introduction

Alto Neuroscience is developing a new generation of precision therapeutics for the treatment of mental illnesses, based on a platform built on large-scale biomarker data, clinical outcomes and cutting-edge artificial intelligence analysis tools. The team combines world-leading neuroscientists, engineers and business executives with a singular focus on transforming the diagnosis and treatment of mental illnesses.

Currently, there is no objective way to diagnose psychiatric illness, nor to identify which treatment is best for an individual patient. Treatment selection is presently done by trial-and-error as there are no reliable blood tests nor objective brain measures, for example, that can inform these decisions. Alto is focused on addressing this need by developing new medications that are more effective by virtue of being personalized -- whereby each person gets the right drug for their brain. Come join us on our mission to reimagine and re-engineer the treatment of mental illnesses!

Job Description

We are looking for a motivated Computational Biologist who is passionate about mental health. This person will work closely with a growing interdisciplinary team of Physicians, Research scientists, Geneticists, and Software developers to challenge the status quo and transform mental health via intelligent use of Artificial intelligence techniques. This position will oversee and perform analysis of large-scale genomic data, and relate these data to a variety of clinical and biological phenotypes. Specifically, this work will include the design and analysis of data to generate actionable patient insights that will aid in personalized treatment for mental health disorders.

Roles and Responsibilities

• Prepare Data and Data pipelines for model development
• Develop novel approaches for exploration, analysis and feature selection from large-scale multidimensional data that include genomics, neurophysiological data, clinical/patient data
• Develop visualization tools to interpret and communicate results
• Use analytic results to generate data-driven, clinically actionable hypotheses and insights
• Build, train, test and deploy machine learning models
• Work closely with software developers to integrate models into software products
• Document code, results and details of the approaches in a thorough and systematic way in order to promote knowledge sharing and code re-use
• Collaborate with other data scientists, SMEs to ideate and solve complex issues pertinent to data ingestion/curation, model performance, model generalization.

Skills and Qualifications

• Master or PhD degree in Computational Biology, Bioinformatics, Genomics, Systems Biology, Engineering, Neuroscience, or other quantitative fields with strong analysis and programming experience.
• Experience analyzing at least one largescale genetics or genomics dataset (e.g. UK Biobank, FinnGen, GTEx, ENCODE, Epigenomics Roadmap, etc.)
• Familiarity with common genomics processing methods and packages for differential expression, including bulk RNA-Seq, single-cell genomics, etc.
• Demonstrated success of biological interpretation, specifically connecting SNPs to genes and/or genes to pathways
• Excellent understanding of machine learning techniques and algorithms
• Experience with common data science toolkits and libraries, such as scikit-learn, Pandas, NumPy, SciPy, PyTorch, etc.
• Programming languages: Python
• Working knowledge of Linux OS, SQL, Git, Docker
• 2+ years of Python programming and product development experience
• 2+ years of machine learning experience using real-world data (Dimensionality Reduction, Clustering, Classification, Regression, Ensemble Methods)
• Strong verbal and written skills, as demonstrated by publications, conference papers, blog posts, etc.
• Familiarity with common genetics processing platforms, such as Hail, is a plus
• Knowledge of genomic data science is a plus
• Knowledge of application of deep learning to real-world data is a plus
• Knowledge of writing Airflow DAGs is a plus

For more information, or to apply now, you must go to the website. Please DO NOT email your resume to us as we only accept applications through our website.