Computational Biologist/Toxicologist

Job Location
Cambridge, MA
Job Description

We are looking for a computational biologist/toxicologist who combines a strong understanding of biological and/or clinical research with sound data analysis skills. The candidate will contribute to preclinical safety teams by:

i)              Aggregating and analyzing a wide range of data types to help answer drug safety questions.

ii)             Building, supporting, and improving informatics tools useful for the analysis and visualization of safety-relevant data.

The candidate must be able to understand existing research challenges and provide an independent perspective on how they might be addressed. They must be able to access and integrate data from multiple sources – both standard toxicology data, as well as data from a number of “omics” platforms – and bring the results to bear on drug safety questions. Paramount to this task is a deep understanding of the underlying biology.

Some of the questions that we routinely address:

  1. What is the likely mechanism of toxicity of compound X, observed in a preclinical study? Is it likely to be on- or off-target? Is it human-relevant?
  2. Which small molecules have produced preclinical safety findings similar to the ones observed with compound X? Do they share a target or mechanism?
  3. What are the predicted safety liabilities of compound X? Or of biologic Y? Or of the inhibition of target Z? How could these potential toxicities be monitored and/or mitigated?

In the age of “Big Data” there are tremendous opportunities to approach these questions and others in novel, more powerful ways.


1-year contract


Computational Biology, Computational Toxicology, in silico Toxicology, Preclinical Safety, Safety Informatics, Health Informatics, Bioinformatics, Cheminformatics, Data Scientist, Data Mining, Machine Learning, Data Analysis, Statistics, Toxicogenomics, Pharmacogenomics.

  1. A Ph.D. in Toxicology, Pharmacology, Biology, Biochemistry, or a related field.
  2. Strong statistical and data analysis skills, including fluency in at least one statistical analysis platform (R strongly preferred).
  3. Familiarity with relational databases, including SQL.
  4. Experience with at least one programming or scripting language.
  5. Fluency in English, including excellent written and verbal communication skills.
  6. Desirable but not required: experience with Spotfire, machine learning, cheminformatics, web development, or KNIME.
How to Apply

Contact Doug Selinger at: [email protected].

About Our Organization

Safety is a major hurdle for drug discovery & development and one of the principal reasons for drug failure. In this era of “Big Data”, large amounts of data have been generated, often without drug safety explicitly in mind, but nevertheless with clear safety relevance. We believe that this represents an unprecedented opportunity to transform drug safety research. Our team is committed to turning this opportunity into a reality. We believe that the result will be a superior drug discovery/development pipeline and better, safer drugs.

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