Bioinformatician, Sable Bio

£50-75k

Python

Git

Junior and Mid level

London

More information about location

1-5 days a week in office (Spitalfields, London)

Comprehensive target safety intelligence in one place

Job no longer available

Comprehensive target safety intelligence in one place

1-20 employees

HealthcareB2BArtificial IntelligenceBiologyMachine LearningSaaSBiotechnology MedTech

Job no longer available

£50-75k

Python

Git

Junior and Mid level

London

More information about location

1-5 days a week in office (Spitalfields, London)

1-20 employees

HealthcareB2BArtificial IntelligenceBiologyMachine LearningSaaSBiotechnology MedTech

Company mission

Navigate target safety with augmented intelligence.

Job

Company

Role

Who you are

PhD or MSc in Computational Biology, Bioinformatics, or related field or BSc with 3+ years of relevant experience applying computational methods to analyse biological data
Strong programming skills in Python
Demonstrated expertise in one or more relevant biomedical domains, such as patient-level data, clinical research, or toxicology
Strong analytical and problem-solving abilities
Excellent documentation and communication skills, with an ability to convey scientific concepts and conclusions to multidisciplinary audiences
Ability to work independently and as part of a cross-functional team
Experience with version control (Git) and Agile methodologies

Desirable

Experience in product development or product-focused environments
Knowledge of toxicology and safety assessments
Familiarity with agile development methodologies
Willingness to become our internal merch designer

What the job involves

Develop and implement computational approaches for analysing complex biological data, to deliver safety-relevant insights for drug discovery workflows
Create and maintain proprietary datasets related to target safety assessment
Contribute to robust data processing pipelines in Python
Collaborate with software engineers to enhance our platform
Contribute to the scientific direction of our product
Help translate biological complexity into actionable insights

Salary benchmarks

Our take

Sable Bio is stepping into an essential area of biotechnology, where drug safety is a top priority. As demand for new, safer medicines rises, toxicity-related issues often slow down drug development, causing costly delays or failures. With AI and data-driven solutions gaining traction, there's a real opportunity to make safety assessments faster and more efficient.

What makes Sable unique is its use of AI to improve drug safety assessments. With this, Sable analyzes various biomedical data sets to detect potential toxicity in new medicines before human trials. By tapping into the scientific literature and diverse data sources, it spots safety risks quicker, helping drug developers make better decisions and save them time and money.

The company has secured substantial funding, which will help it expand its technology and form key partnerships with biotech, pharma, and healthtech companies. As Sable continues to grow, its platform has the potential to transform drug development by reducing risks and improving patient outcomes.

Kirsty

Company Specialist at Welcome to the Jungle

Company

Funding (1 round)

Jan 2024

$2m

Early VC

Total funding: $2m

Company benefits

Every Friday afternoon free for personal development
Private medical plan
Annual training budget for professional development
Opportunity to shape the future of our company and grow as we grow

Company HQ

Spitalfields, London, UK

Leadership

Alex de Giorgio

(Co-Founder & CEO)

Prior to founding Sable, Alex worked at BenevolentAI, leading multiple disease deployments, and pioneering new methods for relationship extraction.

Josh Almond-Thynne

(Co-Founder & CSO)

Prior to founding Sable, Josh helped deliver two pre-clinical candidates as a medicinal chemist at BenevolentAI. He pioneered the use of unstructured data in medicinal chemistry.

Olly Oechsle

(CTO)

Prior to joining Sable, Olly spent eight years at BenevolentAI working on applications, data pipelines and Natural Language Processing (NLP) techniques, as VP of Product Engineering.

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