Proteins are the molecular machines of life, used for many therapeutic, diagnostic, chemical, agricultural and food applications. Designing and optimizing proteins takes a lot of expert knowledge and manual effort, through the use of custom computational and biological tools.
Machine learning is revolutionising this space, by enabling high-fidelity protein models. At Cradle, we offer a software platform for AI-guided discovery and optimization of proteins, so that biologists can design proteins faster and at scale. We are already used by clients across pharma, biotech, agritech, foodtech, and academia.
We're an experienced team of roughly 60 people. We've built many successful products before and have enough funding for multiple years of runway. We are distributed across two main locations, Zurich and Amsterdam, and are focused on building the best possible team culture.
We offer our employees a very competitive salary, a generous equity stake (for full time employees) in the company and a wide range of benefits and career progression opportunities.
We are looking for a motivated Research Associate to strengthen our Large Libraries team. This team is responsible for developing and running high-throughput workflows for generating massive-scale protein libraries and screening them to produce datasets with >10^6 data points. These datasets power our machine learning models to accelerate protein optimization for antibodies, enzymes, and other protein classes. We're building cutting-edge experimental capabilities incorporating technologies like FACS, display platforms (yeast, phage, mRNA), microfluidics, and next-generation sequencing, working hand in hand with our ML algorithms.
As a Research Associate, you'll join a diverse team of researchers to collaboratively execute and continuously improve novel wet lab methods for large-scale library construction, high-throughput screening, and data generation. If you enjoy running protein engineering workflows at scale, love to optimize experimental systems, and want to be a part of building world-class screening capabilities for the next-generation platform for making biotechnological products, please apply!
As a Research Associate in the Large Libraries team, you will:
Run workflows for large-scale library construction, protein display platform preparation (e.g. yeast display, phage display), high-throughput screening (e.g. FACS), and NGS sample preparation.
Operate and maintain high-throughput screening equipment and automation platforms to generate high-quality datasets.
Suggest and work on improvements to make these workflows more efficient, robust, scalable, and integrated with our ML pipeline.
Effectively communicate results, successes, and challenges in a cross-functional environment.
Missing one or two points from the list below? No worries, if you're excited about this role and meet most of these criteria, we definitely want to hear from you.
BSc + 2 yrs, MSc, or equivalent experience in molecular biology, biochemistry, protein engineering, or related fields.
Demonstrated hands-on experience with at least one of the following: yeast display, phage display, mammalian display systems, or other protein library platforms.
Experience with flow cytometry (FACS) or other high-throughput screening methodologies.
Hands-on experience with standard cloning techniques and DNA library construction.
Excitement to learn, contribute, and drive innovation in an early stage startup environment. Having an appetite for its ambiguity and fast pace.
Strong verbal and written communication skills in English. Proactively sharing results, successes and challenges in a cross-functional environment.
Ability to run multiple projects simultaneously while ensuring that process steps are documented, and physical/digital data are organized.
Experience with one or more of the following would be an advantage:
Display platforms (yeast, phage, mRNA, ribosome display, or mammalian display).
Flow cytometry and FACS
Next-generation sequencing library preparation and quality control (Illumina, Nanopore, PacBio).
Microfluidics platforms for high-throughput screening.
Classical high-throughput laboratory automation (robotic liquid handlers, plate readers, colony pickers).
High-throughput cloning technologies, such as site-directed mutagenesis, Gibson Assembly, Golden-Gate Cloning, or overlap extension PCR.
Large-scale library construction methodologies (>10^6 variants).
Familiarity with (scripting) languages such as Python, Matlab, R, SQL.
Experience with statistical experimental design or data quality assessment.
Learning more about the BioEngineering team
We're quite open about what we work on in our BioEngineering team. If you'd like to learn a bit more before applying, check out blog posts from our team (link 1, link 2) or watch our webinar on lab automation.
A notice about recruitment scams: Please be aware that scammers are posing as us in order to get your personal details or money. We only communicate via @cradle.bio email addresses, we only make job offers after having met you in person at our office in Zurich or Amsterdam, and we never ask you to pay for anything during the interview process.
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