Candel Therapeutics is a clinical-stage public biotechnology company pioneering the development of viral based immunotherapies for the treatment of solid tumors. Candel's products are designed to help patients fight their cancer while maintaining quality of life - from early-to late-stage disease.
Join our rapidly growing company where you will wear multiple hats in an environment that values innovation, scientific rigor and a "can do" attitude. We care about our team, our patients, and our community. We have a robust pipeline with clinical assets in phase 1, 2 and 3 for the treatment of prostate, brain, lung and pancreatic cancers. Candel is a newly public company having completed its IPO at the end of July 2021. Please visit www.Candeltx.com for additional information.
The Discovery group is seeking an innovative leader in computational biology to join the newly created Discovery Team at Candel Therapeutics. The candidate will lead the establishment of the advance analytic platform that will supports Candel Discovery efforts and asset design. The candidate will support the design of a series of high-dimensional bioinformatics projects aimed at profiling different tumors, integrating multimodal experimental data derived both from internal and external data sets. The data generated will be channeled in a series of proprietary biological assays and the candidate is expected to apply machine learning algorithms to select optimal target gene combinations for specific indications.
The successful candidate will support a team of immunologists, biologists and virologists in the identification of the optimal cargo for Candel's next generation viral immunotherapies. The candidate is expected to lead these activities in a largely externalized model via computational biology and artificial intelligence providers. This role will require strong leadership, creativity, independence and a strong collaborative attitude.
- Identify distinct tumor signatures, that can be leveraged therapeutically, in samples of patients undergoing experimental cancer immunotherapy or in publicly available multi-modal omics datasets, utilizing integrative bioinformatic approaches
- Work with advanced genomic data (single cell multi omic data, RNAseq, TCRseq, WES) to evaluate contribution of specific pathways or cell type to self response to tumor.
- Design experiments and support data analysis through externalized bioinformatic providers.
- Apply machine learning algorithms to internally generated experimental datasets to enable selection and modelling of optimal gene combination for a new generation of viral immunotherapies.
- Develop an innovative analysis pipeline that will underpin Candel new discovery platform.
- Identify, develop, manage, and contribute to collaborations and partnerships.
- Document and organize experimental procedures and results; generate experimental reports.
- Synthesize and integrate results across experiments and present to colleagues and senior management.
- Work cross-functionally with internal key stakeholders including vectorology, biology, immunology and experimental medicine.
- Facilitate interactions with external partners and CROs to advance discovery and experimental medicine programs.
- Contribute to a dynamic, fast-paced scientific culture that embraces creativity and innovation.
- Ph.D. in bioinformatics, computational biology, systems biology/immunology, or a related discipline with a strong record of publications/patents is required.
- Industry or academic experience as senior or principal scientist or Lead of a computational biology team.
- Experience developing and optimizing NGS-based analytical tools for cancer and/or immunology.
- Familiarity with single-cell sequencing approaches, proteomics based assay analysis and data analysis would be is a significant plus.
- Use of Linux in a cluster-computing environment.
- Fluency in R and/or Python.
- Demonstrated ability to formulate and test hypotheses for potential targets or biomarkers by designing and implementing novel computational approaches and Machine Learning approaches.
- Experience with mining public data sets.
- Excellent written and verbal skills; ability to translate and communicate complex information and concepts for scientists of diverse backgrounds.
- Positive and collaborative attitude; ability to work in a largely externalized model with external collaborators and multidisciplinary teams.
- Capacity to prioritize and work independently to complete tasks and advance projects with minimal supervision.
- Creative and innovative thinking; track record of thought leadership.
- Excellent attention to detail, communication skills, and flexibility.