Head of AI-ML and Bioinformatics

ProQR Therapeutics

Leiden, Netherlands

ProQR is seeking a new leader for the AI and bioinformatics group, overseeing and steering all of ProQR’s data management, bioinformatics, machine learning and (generative) artificial intelligence activities. At ProQR we generate large quantities of platform data and have sizable ambitions in leveraging this data to accelerate our research to create better medicines for patients. As the leader of the bioinformatics and AI group you are collaborating with all teams throughout the R&D organization to generate, store and analyze data in the most efficient and impactful way to gain insights that help drive our research and development of medicines forward. This leadership role requires you to design and articulate a strategy that is fit for purpose and lead implementation and operation thereof.

Key Responsibilities

Data Strategy and Governance:

Develop and implement a comprehensive data strategy aligned with ProQR’s R&D and business objectives, particularly focusing on enhancing preclinical capabilities.
Establish and enforce data governance policies, standards, and procedures to ensure data quality, security, and regulatory compliance.
Define data architecture and infrastructure requirements to support current and future needs, integrating advanced AI/ML technologies.

Data Management:

Oversee the collection, storage, processing, and analysis of structured and unstructured data from internal and external sources.
Implement data management best practices and technologies to optimize data workflows, storage, and accessibility, with a strong focus on preclinical research data.
Drive initiatives to improve data quality, integrity, and accessibility across the organization, ensuring seamless integration of AI/ML tools.

Data Analytics and AI/ML Insights:

Lead efforts to derive actionable insights from data through advanced analytics, machine learning, and data visualization techniques, enhancing drug discovery and development.
Collaborate with business stakeholders to identify opportunities for leveraging data and AI/ML to drive business growth, improve operational efficiency, and enhance research outcomes.
Develop and communicate data-driven recommendations and AI/ML insights to key stakeholders to support strategic decision-making in preclinical and clinical research.

Leadership and Collaboration:

Build and lead a high-performing team of data professionals, including consultants, data AI/ML experts, and bioinformaticians.
Collaborate with executive leadership, R&D and IT teams to align data and AI/ML initiatives with overall business strategy and priorities.

Who are you?

Passion for AI/ML: You are passionate about AI/ML and its transformative potential in the biotech and pharmaceutical industries, with a deep understanding of its applications in preclinical research.
Education: Bachelor's degree in Computer Science, Data Science, AI/ML, Statistics, or a related field; advanced degree preferred.
Experience: Minimum 10 years of experience in Data Management, analytics, and AI/ML, with a minimum of 2 years leading a team of people. More senior leadership experience would be a plus.
Strategic Thinking: Ability to think strategically, drive innovation, and translate business requirements into data and AI/ML solutions that enhance preclinical research and development.
Technical Skills: Strong understanding of AI/ML principles, techniques, and technologies, including deep learning, neural networks, natural language processing, and predictive modeling. Experience with AI/ML frameworks and tools.
Data Management Expertise: Strong understanding of data management principles, techniques, and technologies.
Data Governance: Expertise in data governance frameworks, regulatory compliance, and privacy regulations, particularly in the biotech and pharmaceutical sectors.
Programming: Knowledgeable in programming languages, data analysis tools, and data technologies.
Communication: Excellent communication, leadership, and stakeholder management skills, with the ability to convey complex data and AI/ML concepts to non-technical stakeholders.

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