Bioinformatics Engineer

1 week ago

Toronto Ontario, Ontario, Canada Bridge Informatics Full time

Job Role: Bioinformatics Engineer

Location: Toronto, ON

Contract Type: 12-month contract, Full Time, Hybrid


Company Description

At Bridge Informatics, we specialize in developing custom data-driven solutions for life science customers. Our mission is to bridge the gap between bench researchers and bioinformaticians, practice and theory, and data and insight to provide efficient, interdisciplinary solutions for our clients. Join our team and work on innovative projects that advance precision medicine.


Our work environment includes:


  • Remote, work-from-home in Ontario or Canada in general, with quarterly trips to the Greater Boston area.
  • Dedicated focus on communication, trust, empathy, and expertise.


Role Overview:


The successful candidate will embark on a year-long, full-time engagement with a prominent pharmaceutical client, fully embedding themselves within the client's discovery research team. This team spans a diverse range of therapeutic and functional areas, including computational biology, oncology, immuno-oncology, and chemistry. While based remotely, the candidate will make quarterly visits to the client's Cambridge, MA site, fostering close collaboration and knowledge sharing. Their primary responsibility will be analyzing data from functional genomic screens to discover and validate both tumor-intrinsic and microenvironmental targets crucial for overcoming resistance to targeted immunotherapies.


Role Description


  • This is a full-time hybrid role, primarily as a remote employee working from home, with limited onsite visits to greater Boston, MA.
  • Day-to-day tasks include statistical analysis, DNA/RNA sequencing data analysis, and extracting insight from functional genomic screening results using R.
  • The candidate will work with their team to design and develop existing (or custom) bioinformatics pipelines and data dashboards to extract insight from the data and discuss it with scientists of different training.


Please note: The ideal candidate needs to be focused on extracting insight from the work with scientists of different backgrounds and not necessarily a perfectionist in creating production-level tools. For this reason, we look highly upon those with previous work at the bench. Ideally, this candidate has experience optimizing assays and understands the importance of basic lab skills, such as when and why one should use positive and negative controls.


In this exciting role, you will be…


  • Assisting in the continuous experimental design of statistically powered CRISPR screens in vitro and in vivo.
  • Conducting statistical and bioinformatics-based analyses of functional genomic screens to decipher genes/pathways that influence key biological processes or therapy resistance/response mechanisms.
  • Creating and employing advanced statistical methods to define functionally important signaling network disturbances through the analysis of pooled CRISPR screening with single-cell transcriptomics (CROP-seq, Perturb-seq).
  • Utilizing bioinformatics methodologies to consolidate the findings from functional genomic screens with other biological data streams for target identification, prioritization, and biological hypothesis generation.


You will also be able to


  • Think out loud in an open manner, fostering open communication and collaborative problem-solving within cross-functional teams.
  • Translate biological hypotheses into testable computational investigations, leveraging functional genomics data and multi-omics molecular profiles in collaboration with discovery research teams.
  • Understand the underlying biology of a given functional genomics screen, and be able to apply that understanding during decision points in data analysis.
  • Proactively engage with the latest advancements in single-cell and functional genomics analysis, critically reviewing emerging bioinformatics methodologies and algorithms, and introducing and implementing suitable approaches within the research environment.
  • Recognize, analyze, and integrate diverse internal and external data sources and knowledge resources to facilitate data mining within a biological context, informing target validation and mechanism of action studies.
  • Effectively support client project management through proactive coordination of internal and external collaborators, ensuring seamless execution of research initiatives.


Required Qualifications & Skills:


  • Extensive experience with using R for analysis and visualization of large, complex biological datasets.
  • Experience in R Shiny, including demonstrated skill in building upon and extending existing applications developed by other scientists.
  • Comprehensive understanding of CRISPR screen data processing, encompassing the ability to efficiently process, analyze, and store large datasets in an automated manner.
  • Deep familiarity with high-throughput genetic screening data, coupled with the capacity to propose and implement strategies for computational and biological validation in collaboration with therapeutic area partners and collaborators.
  • Proven ability to operate effectively within a highly collaborative environment, seamlessly integrating into project teams that span scientific disciplines (genetics, pharmacology, chemistry, molecular biology) to accelerate innovative drug target discovery.
  • Demonstrated expertise in collaborating with experimental scientists to characterize novel targets identified through genetic, translational, and disease pathway exploration, including target engagement assessment, mechanism of action research, and functional validation.
  • Exceptional written and verbal communication skills, ensuring clear, professional, and effective information exchange with colleagues, collaborators, and stakeholders.
  • Possesses strong emotional intelligence, demonstrating self-awareness, empathy, and the ability to navigate interpersonal dynamics effectively within a team setting.


Required Education:


  • Ph.D. (or 5+ years of relevant experience) in Bioinformatics, Biostatistics, Computational Biology, Computer Science, Genetics, Immunology, Mathematics, Molecular Biology, or a related field.


Preferred Experience and Skills:


  • A strong foundation in immunology or cancer biology, with demonstrated critical thinking skills applied to experimental design, statistical hypothesis testing, and biological interpretation.
  • Proven ability to integrate information from diverse sources to strengthen research hypotheses and drive scientific discovery.
  • Experience with high-performance Linux clusters and cloud computing environments (e.g. AWS), enabling efficient data analysis and management. Familiarity with machine learning or statistical inference techniques is highly advantageous.
  • Knowledge of basic software development principles, such as experience with using Git/GitHub for version control and collaboration, an understanding of code documentation, and the ability to debug pre-existing code.
  • A strong team player with excellent emotional intelligence, capable of thriving in collaborative settings while also possessing the initiative and focus to excel independently.
  • Prior professional experience within a pharma/biotechnology setting (outside of non-profit or academic institutes), demonstrating a deep understanding of the unique demands and opportunities of this dynamic industry.


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