Computational Proteomics Scientist at Cedilla Therapeutics
Cambridge, MA, US

We are looking for a computational proteomics scientist

We are looking for you!

We are an energetic new company focused on harnessing intrinsic protein stability mechanisms to broaden the reach of small molecule therapeutics. By working on cancer and other diseases caused by protein dysregulation, we have an opportunity to create unique and valuable new medicines.

You are a data scientist with expertise in proteomic analysis or related computational biology skills. You will be key in integrating internal and public data from proteomics experiments with chemical and genetic screens enabling the discovery and validation of new targets as well as contributing to our understanding of protein interactomes and molecular mechanism of action for targets and candidate therapeutic chemical entities. You will work closely with other data and experimental scientists in our interdisciplinary team to influence decision-making and research directions.

We view you as a key leader/scientist in the company, whose contributions will be critical to the success of our endeavor.

Those contributions would include:

  • Analyzing quantitative high-resolution mass spectrometry (qHRMS) proteomics data for unbiased and targeted proteomics experiments.
  • Successfully using data management tools and applications for quantitative proteomics research. With an ability to combine open-source and/or commercially available software platforms, you will be responsible for enabling protein identification, annotation, enrichment and functional analysis at a system level across multiple biosamples (e. cell lines and tissues).
  • Understanding quantitative multiplexed proteomics and chemo-proteomics workflows and data structure to efficiently integrate and/or develop automated data acquisition, processing, analysis and visualization protocols, with appropriate infrastructure and pipeline management tools.
  • Identifying and integrating relevant systems analysis tools and algorithms for data and knowledge resources to enable mining in biological context.
  • Using statistics and machine learning to provide analyses of complex datasets to facilitate drug discovery.
  • Facilitating scientific insights in conjunction with experimental scientists by integrating information generated from multiple sources to shape and strengthen research hypotheses.

Highlights of your background include:

  • Ph.D. or B.S./ M.S. equivalent with 5+ years of experience with a focus on computational biology and bioinformatics, applied to proteomics or related biological data scientific field.
  • Proven track record in the analysis, visualization and interpretation of large proteomics data sets. Experience with other large “omics” data sets is a plus.
  • Solid understanding of statistics and expertise in R and Python.
  • Experience with protein post-translational modification PTM) analyses (e. phosphorylation, ubiquitination, etc.) is preferred.
  • Experience processing, analyzing and interpreting proteomics data generated via peptide-labeling (e. TMT®, SILAC, etc.) and label-free approaches.
  • Familiarity with Integrated Proteomics Applications (IP2) software, ProLuCID, DTAselect or other similar relevant search engines required.
  • Hands-on experience in intra-/ inter-experiment knowledge integration to define interactome networks, co-regulators, upstream/downstream regulators, pathway and substrate analysis, etc.
  • Familiar with systems (chemical) biology concepts. Experience building molecular phenotyping-perturbagen connectivity maps at protein level and integration of protein-ligand binding profiles and cellular functional profiles. Able to combine protein and pathway annotation and analysis with perturbagen affinity enrichment data to enable deep understanding of ligand-proteome affinity relationships.
  • Skilled in network analysis, data mining and visualization tools, with knowledge of human genome annotation and biological pathway resources such as: StringDB, IPA, MetaCore, GO, GSEA, DAVID, KEGG,
  • Good command of common data analysis and visualization tools such as TIBCO Spotfire®. Previous experience in the analysis, visualization and interpretation of large “omics” data sets as well as integration with chemical and biological data is highly desirable. Previous experience on Pipeline Pilot is a plus.
  • Familiar with best practices of software development, with understanding of SQL/NoSQL database schemas and development, MongoDB, XML, RDF, neo4j, or equivalent. Proficient in programming languages (Python and JAVA/JavaScript) in a Unix/Linux environment. Experience with high-performance Linux cluster and cloud computing.
  • Experience in statistics, including familiarity with mathematics and statistics packages such as R/Bioconductor. Familiarity with new machine learning techniques is a plus.
  • Creative and independent scientific thinking to solve complex technical and scientific problems.
  • Highly self-motivated, with excellent attention to detail and strong organizational and communication (oral and written) skills. Ability to work independently, yet team-oriented and capable of building strong relationships with peers, customers and partners/collaborators. 

You are not just an amazing computational proteomics scientist, you’re the whole package!

How do I apply?

Please send your resume and anything else you would like to share to

About Us

Cedilla is leveraging a growing understanding of the principles that dictate protein stability and applying those principles to target proteins that drive cancer and other diseases. Cedilla’s integrated product engine includes target-centric and unbiased approaches and is designed to produce small molecule therapeutics that degrade protein targets. Although degradation by small molecules has been observed serendipitously, degradation as a mechanism of action has not been pursued systematically in small molecule drug discovery.

We were launched in April 2018 and are backed by Third Rock Ventures.