About EDDC:
EDDC is a National platform dedicated to developing innovative therapies that transform patients lives. Our research and development efforts are focused on uncovering the underlying mechanisms of disease and translating this knowledge into impactful treatments. We work collaboratively with public sector and industry partners to translate scientific discoveries arising from Singapore's biomedical and clinical sciences R&D into innovative healthcare solutions, with a focus on Asian-prevalent diseases.
Position Overview:
We are seeking a talented and motivated AI-Driven Antibody Design Scientist to join our interdisciplinary team. In this role, you will develop and apply state-of-the-art machine learning (ML) models to design and optimize antibodies, driving innovation in therapeutic discovery. You will collaborate closely with wet-lab scientists, computational biologists, and cross-functional teams to accelerate design-build-test cycles and deliver transformative antibody solutions.
Key Responsibilities:
- Develop and apply sequence- and structure-based ML models to design antibodies with optimized properties, including efficacy, specificity, and developability.
- Engineer ML models to predict and enhance antibody-antigen interactions, enabling targeted and data-driven antibody design.
- Collaborate with wet-lab teams to integrate experimental data into ML pipelines, iteratively refining models to improve predictive accuracy and design outcomes.
- Lead the end-to-end development of ML pipelines, including data acquisition, preprocessing, model training, validation, and deployment.
- Stay at the forefront of AI/ML advancements and antibody design innovations, identifying opportunities to enhance internal capabilities and workflows.
- Communicate complex ML concepts and results effectively to interdisciplinary teams, fostering collaboration and driving project success.
Qualifications:
- PhD (preferred) or Master?s/Bachelor?s degree in Computational Biology, Machine Learning, Bioinformatics, Biophysics, or a related field. Exceptional candidates with relevant experience will be considered.
- Proven track record of leading machine learning research projects that resulted in impactful tools, publications, or advancements.
- Strong foundation in statistics, machine learning, and deep learning, with hands-on experience in developing, training, and tuning models.
- Proficiency in Python, PyTorch, and ML frameworks for model development and evaluation.
- Experience with Unix/Linux environments, cloud platforms (e.g., AWS), and version control tools like GitHub.
- Ability to thrive in a fast-paced, collaborative environment, with a problem-solving mindset and attention to detail.
- Strong interpersonal skills, with a team-first attitude and a commitment to mentoring junior team members and fostering innovation.
Preferred Skills:
- Experience working with protein sequence/structure data or related computational biology tools (e.g., Rosetta, AlphaFold, etc.).
- Knowledge of antibody engineering, immunology, or therapeutic development workflows.
- Familiarity with NGS data analysis and integrating experimental datasets into ML pipelines.
- Excellent communication skills, with the ability to translate complex technical concepts into actionable insights for diverse audiences.
Why Join Us?
- Work at the intersection of AI, biology, and drug discovery, tackling some of the most exciting challenges in biotechnology.
- Collaborate with a passionate, interdisciplinary team of scientists and engineers.
- Access to cutting-edge tools, technologies, and resources to drive innovation.
Competitive compensation, benefits, and opportunities for professional growth
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