Data Scientist, AIDD/Prescient Design, CS-CoE

Full time contractor position (40h per week), up to 12 months

At Roche, we believe it is critical to deliver medical solutions now – even as we develop innovations for the future. We are passionate about transforming patients’ lives and we are fearless in both decision and action. And we believe that good business means a better world.

That is why we come to work each day. We commit ourselves to scientific rigor, unassailable ethics, and access to medical innovations for all. We do this today to build a better tomorrow.

Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche’s Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness the transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide.

Position 

The Structure-Function ML group within Prescient Design / (AIDD - AI for Drug Discovery), CoE, a division devoted to developing machine learning-based methods for de novo antibody design, seeks exceptional Data Scientist with background in protein structural biology and machine learning, a passion for research and technical problem-solving, and a proven ability to implement ideas and apply methods. 

The successful candidate will contribute to our antibody design efforts, partner with structural computational biologists, machine learning scientist & engineers, technologists and drug discoverers (in New York, San Francisco and Basel) to enable end-to-end data workflows for large-scale data ingestion, processing, analysis, and modeling with our core machine learning frameworks.

Responsibilities:

As a Data Scientist, AIDD/Prescient Design, CS-CoE, you will:

Enable cutting-edge research in machine learning and applications to drug discovery, design, and development through the collection, design, and management of data pipelines and infrastructure

Operationalize models leveraging AWS services and design optimal architectures for data science projects in AWS

Execute computational and statistical analysis of single B cell data analysis, antibody structure prediction/analysis, visualization and presentation of large data sets in support of our de novo antibody design and lab-in-the-loop efforts

Collaborate extensively with cross-functional teams across Roche including antibody engineers and experimental scientists to support data ingestion and development of dataflows

Build and strengthen relationships with other departments/groups across Roche to identify synergies and streamline redundancies; create and manage documentation for different data science / data engineering projects

Be expected to help develop, manage, and scale data pipelines and infrastructure for analysis and modeling in production

Requirements & Qualifications

• B.S., M.S., or Ph.D. in Computer Science, Statistics, Applied Mathematics, Computational Biology, Physics, related technical field, or equivalent practical experience
• Strong, demonstrable experience of using computational methods to analyze protein structure and function or antibody repertoire analysis for antibody engineering and decision support
• At least one-year relevant work experience
• Strong programming skills in languages like C++, Python, Java, Scala, or SQL and experience with scientific computing software and scripting languages
• Profound knowledge in Python (pandas, tensorflow, numpy, etc.)
• Experience developing and maintaining codebases and software libraries, following industry’s best practices
• Intense curiosity about the biology of disease and eagerness to contribute to scientific and computational efforts
• Deep understanding and hands-on experience on construction or modification of AI/ML and computational applications in large molecule drug discovery, for example:
• protein structure prediction (e.g., AlphaFold),
• protein sequence design and inverse folding (e.g., ProteinMPNN),
• computational protein modeling, design, and analysis (e.g., Rosetta).
• Reference: hPxO6GGxmFDQkbJ-_aIO-vkSuXLzGYSGoa6Chug7v-E_0zH0mFrM83wzNm_CtSh8
• Prior experience or familiarity working with protein sequence and/or protein structure data or familiarity with experimental data from biology, immunology or related disciplines
• Experience in physics-based modeling tools i.e. molecular dynamics, docking or Rosetta
• Public portfolio of computational projects (available on e.g. GitHub)

Should you answer the above challenges and requirements with YES then this is the right position for you!

Who we are

At Roche, more than 100,000 people across 100 countries are pushing back the frontiers of healthcare. Working together, we’ve become one of the world’s leading research-focused healthcare groups. Our success is built on innovation, curiosity and diversity.

We believe in the power of diversity and inclusion, and strive to identify and create opportunities that enable all people to bring their unique selves to Roche.

Roche is an Equal Opportunity Employer.