Dewpoint Therapeutics translates condensate biology into much-needed medicines. Biomolecular condensates are transforming our understanding of biology, and our highly collaborative team is at the forefront of efforts to harness this shift for drug discovery. Together, we are leveraging this transformation in understanding of cellular biology to discover and advance breakthrough therapies for the toughest diseases.

We are searching for a (Senior) ML/AI Data Scientist with strong experience in deep learning and AI to develop and productionize innovative models that enhance and accelerate our drug discovery and clinical translation efforts. The core focus of the data scientist role is on building and applying cutting-edge ML and AI models that optimize analysis of wet lab experiments and make predictions that guide future experiments. The role is part of a team of data scientists and engineers working on models spanning the end-to-end R&D process and multiple data modalities, including imaging, omics, chemical structure, and medical record data. Success in the role will require hands-on experience developing and refining deep learning models in a relevant domain or data type, a pragmatic ‘test and learn’ mindset, and the ability to collaborate effectively with biologists and chemists to tailor analysis to specific scientific contexts. In building models that transform Dewpoint’s drug discovery process you will be helping transform lives by contributing to the discovery of revolutionary new therapies.

In this position you’ll be part of a purpose-driven and supportive startup team culture, engaged in continuous learning, and part of an exceptional international team. The role is within our Data Science and Engineering group, reports to the Head of Data Science and Engineering, and can be based in Boston’s Seaport district, in London, or in Dresden. Dewpoint offers competitive salaries and great benefits.

In this role, the key responsibilities will be:

Working with biology, chemistry, and clinical subject matter experts to translate research questions into appropriate data science methods
Developing, testing, and iterating data science solutions, including of advanced methods (such as deep learning models, transformers, weak- and self-supervision, fine-tuning of foundation models, generative methods etc.)
Communicating results effectively to subject matter expert colleagues, and iteratively refining methods to ensure appropriateness for specific research programs and experiments
Collaborating with colleagues in a team setting to productionize effective methods into reproduceable and scalable pipelines while ensuring high software engineering standards
Owning delivery of data science workstreams end-to-end, potentially including the mentoring and coaching of junior colleagues
Continually learning and growing as a data scientist, keeping up to date with the latest developments in methods
Contributing to building technical capabilities and standards across the organization

To do this, you will need:

Master’s degree or doctorate in an appropriate field, such as data science, computer science, applied statistics, mathematics, or equivalent
Experience applying machine learning models in an appropriate biological domain or equivalent data context, such as on imaging or chemical structure data
Experience building, refining, or applying deep learning models, such as fine-tuning foundation models for predictive tasks or embedding generation
Strong experience writing code in Python, and with appropriate deep learning packages such as PyTorch, TensorFlow
Experience developing, debugging, and applying deep learning models in the cloud using GPUs, ideally on AWS
A pragmatic and entrepreneurial mindset, and be able to efficiently explore alternative approaches to deliver an appropriate solution
Proven track-record of strong analytical and problem-solving skills
Strong collaboration and communication skills, with the ability to work effectively with colleagues with a range of technical expertise and seniorities

Also nice to have would be:

Experience working with code management tools (Git) in collaborative team environments
Experience in generative methods, particularly in the field of structural (small molecule) chemistry
Experience with best practice software engineering practices, such as reusability, modularity, testability etc.
Experience productionizing models in the cloud, ideally including the use of scalable technologies such as cluster computing and containerization
Experience working in parallel / scalable languages such as Spark or Dask
Experience working with knowledge graphs and graph neural networks
Biotech or biopharma experience, ideally within R&D
Experience in a startup or scale-up environment

Dewpoint Therapeutics is the first company founded to apply the emerging discipline of biomolecular condensates to drug discovery. Dewpoint believes that a vast range of conditions have pathways that are regulated by condensates or arise from the dysfunction of condensates — including cancer, neurodegeneration, and metabolic disease. Dewpoint scientists are working in Boston, MA, and Dresden and Frankfurt, Germany, to translate condensate biology into treatments for the toughest diseases.

Dewpoint Therapeutics is an equal opportunity employer committed to the principles of non-discrimination in the workplace. Candidates will not be discriminated against because of age, race, creed, color, religion, sex, sexual orientation, national origin, disability, marital status, or any other basis prohibited by federal, state, or local law.

Please, no solicitations by agencies.

Dewpoint Therapeutics

New Jobs

ML/AI Data Scientist