Website Dewpoint Therapeutics
The Condensates Company
Dewpoint Therapeutics is building a highly collaborative team to harness the power of biomolecular condensates. Together, we are leveraging a transformative shift in the understanding of cellular biology to discover and advance breakthrough therapeutics for the toughest diseases.
We are seeking Statistical Geneticist at the Scientist or Senior Scientist level to help Dewpoint further our vision and be a part of a new cutting edge group to leverage human genetics, genomics, and computation to translate high throughput measurements in condensate biology to actionable knowledge about disease, patients and therapeutics. You will conduct novel analyses such as genome-wide association studies, fine mapping using large biobank data sets, characterization of structural variation, shared heritability, linkage analysis and colocalization between traits. The results of such studies increase confidence in the causal biology of condensate mediated diseases. A key focus of the role will be the identification of appropriate data sets as well as the design and execution of analyses to realize the promise of modern human genetics in increasing the probability of successful drug discovery.
This position will report to the VP, Computational Biology and Human Genetics, and will work collaboratively across disciplines with biologists, chemists, and technologists, leading to therapeutic discoveries.
In this position you’ll be part of an energizing and supportive startup culture engaged in continuous learning, and part of an exceptional international team. This role is based at our site in Boston's Seaport district. Dewpoint offers competitive salary and benefits.
In this role you will…
- Design and perform integrative analyses that combine human genetics with phenotypes and molecular data
- Identify or prioritize therapeutic hypotheses (targets, tissue/cell types, strata, mechanism) for multiple indications of interest
- Work with experimental biologists and analytical scientists to provide input on experimental design for target validation (in vivo and in vitro model systems, cell types)
- Work with and help facilitate interaction with external partners in academia and industry
- Develop novel methods integrating human genetics and ‘omics and condensate data
- Participate in and oversight of scientific report writing
- Present methods, results, and conclusions to a publishable standard
- Become a valuable contributor to other initiatives as they arise in our fast paced, start up environment
To do that you will need…
- A Ph.D. in genomics, genetics, bioinformatics, or a related field
- Expertise in statistical genetics, especially experience with GWAS or QTL mapping
- Experience with relevant programming/scripting tools (e.g. R, Python, C/C++), Linux/Unix
- Experience devising, testing and validating novel methods using analytics
- Demonstrated ability to build strong working relationships that facilitate effective collaboration across cross-functional teams
- Track record of excellent interpersonal and communication skills, including ability to provide concise summaries of complex data to empower decision making
- Ability to communicate effectively in English, the shared language of our multicultural team
It is nice but not essential that you also have…
- Experience with “post-GWAS” integrative analyses (e.g. DEPICT, DAPPLE, Mendelian randomization)
- Knowledge of functional genomics data, e.g. single-cell RNAseq and epigenetic data (ATACseq, CHIPseq, etc.)
- Experience with biobank data and deep phenotyping (ICD9,10)
- Experience with cloud environments (e.g. AWS, Google Compute, Azure), cloud platforms (e.g. Databricks)
- 2+ years experience in the pharmaceutical industry and/or with drug development
Dewpoint is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.
To apply for this job please visit boards.greenhouse.io.