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Head of Platform Technology

About Us

Deep Genomics is at the forefront of using artificial intelligence to transform drug discovery. Our proprietary AI platform decodes the complexity of RNA biology to identify novel drug targets, mechanisms, and therapeutics inaccessible through traditional methods. With expertise spanning machine learning, bioinformatics, data science, engineering, and drug development, our multidisciplinary team in Toronto and Cambridge, MA is revolutionizing how new medicines are created.


About the Role

Reporting to the CSO, the Head of Platform Technology will define, grow, and manage a team responsible for evaluating, integrating, and advancing our NGS, genomics, molecular biology, and cellular technology capabilities.  The team is responsible for applying these methods to generate high quality, proprietary, multi-omics data at scale for training and validation of AI capabilities for uncovering pathway biology and new biological mechanisms, novel target ID, and optimization of nucleic acid therapeutics.  This is a highly innovative position that requires a deep understanding of NGS method development, genomic data generation, molecular biology, screening technologies, and a passion for developing cutting-edge genomic technologies. It also requires the ability to build production scale pipelines leveraging automation as appropriate to achieve scale, throughput, and reproducibility.  You will work closely with the Machine Learning, Platform Biology, and Computational Biology teams to design experiments, analyze NGS data, and help interpret results for cross-functional teams.


Key Responsibilities
  • Work cross-functionally with internal stakeholders to define and execute a strategy that grows the AI platform to unlock new genetic medicines.
  • Build and lead a team of scientists dedicated to the development and implementation of sequencing, molecular profiling, and assay technologies across single-molecule and cellular assays to broad -omics applications.
  • In collaboration with the Machine Learning team, identify opportunities, set strategy, and lead execution of projects for generation of large scale multi-omics data in disease-relevant contexts for model training validation. 
  • Build an environment & culture focused on generating high quality proprietary data, and create a tight feedback loop between modeling & experiment through close collaboration with the machine learning, Target ID, and Platform Technology teams. 
  • Work with the computational biology and engineering teams to develop analytical methods and ensure efficient data capture through the ELN system and Deep Genomics Nexus platform.
  • Contribute to key corporate initiatives by supporting business development activities as well as identifying opportunities to access relevant data sets through strategic partnerships.
  • Demonstrate strong leadership, personal accountability and interpersonal skills, and capability for mentoring (direct reports & others).
  • Present data and strategy to scientists and management in internal and external venues and publish in peer-reviewed journals as appropriate.


Basic Qualifications:
  • PhD in biological sciences with 15+ years of post-graduate experience in relevant roles (or equivalent) leveraging genomics technology in early stage drug development.
  • 8+ years building, managing, and leading teams to meet goals of the organization, partners, and patients.
  • A creative thinker with a “platform attitude” and direct experience developing and executing high-quality cell profiling assays and screens using various technologies in an advanced data and computing environment.
  • Experience with quantitative analysis of on-/off-target effects and cell penetrance as applied to genetic medicines including, ASOs, gene editing, & gene therapy.
  • Experience with automation and employing analytical, computational, and statistical methodologies to enhance development workflows.
  • Proficiency in multiple of the following: phenotypic assays, gene editing, automation, high throughput qPCR/ddPCR,high-content imaging, and -omics technologies.
  • Deep molecular biology expertise with experience in state-of-the art methods for large scale library production & screening using barcoded technologies including MPRAs, Pertub-seq, and other similar technologies.
  • Proven ability to work independently and cross-functionally with highly skilled teams in a fast-paced, entrepreneurial, and technical environment.
  • Strong managerial qualities, including a strategic and scientifically oriented mindset, attention to detail, strong organizational skills, emotional intelligence, credibility, integrity, creativity, and a willingness to have ideas challenged by team members and to challenge them.
  • Ability to organize and communicate complex data sets in a clear and concise manner to key stakeholders from diverse backgrounds.
  • Prior experience working with or leading collaborations with external biotechnology, academic, and contract research organizations.


Preferred Qualifications:
  • Background in a scientific field involving quantitative modeling, such as biophysics or computational chemistry.
  • Direct experience with building novel screening pipelines using single c.
  • Experience with additional high throughput methods including quantitative imaging, proteomics, and functional genomics is highly beneficial.
  • Familiarity with oligonucleotide chemistry and analytic methods would be beneficial.
  • Strong computational background or demonstrated ability to interface with computational biology teams to develop computational pipelines for analysis of genomics data.
  • Experience with multi-site project management and team leadership.


What we offer:
  • A highly competitive salary, a meaningful equity ownership stake in Deep Genomics, and exceptional opportunities for learning and growth.
  • Company paid benefits.
  • You’ll also be joining a bright, collegial, highly-motivated group working at the intersection of two of the most exciting areas of science and technology: AI and biotechnology.



Deep Genomics welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.


Deep Genomics thanks all applicants, however only those selected for an interview will be contacted.

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What You Should Know About Head of Platform Technology, Deep Genomics

Deep Genomics is seeking a Head of Platform Technology in Cambridge, MA, who will play a pivotal role in transforming drug discovery using artificial intelligence. This exciting position, reporting directly to the CSO, involves building and managing a team dedicated to evaluating and advancing our capabilities in NGS, genomics, and molecular biology. As the Head of Platform Technology, you'll engage with various teams to generate high-quality, multi-omics data for model training and novel target identification. Your work will include defining and executing strategies to unlock new genetic medicines, fostering a culture of innovation, and ensuring that our AI platform continues to grow. You'll also collaborate with the Machine Learning and Computational Biology teams to analyze data and design experiments. A deep understanding of genomic technologies and the ability to lead cross-functional initiatives are essential. This role offers fantastic growth potential, competitive salary, and a meaningful equity stake at Deep Genomics, where you can truly make a difference in the biotechnology sector. If you are a creative thinker with strong leadership skills excited about machine learning and molecular technologies, we want you to join our passionate team and help us revolutionize how new medicines are developed.

Frequently Asked Questions (FAQs) for Head of Platform Technology Role at Deep Genomics
What responsibilities does the Head of Platform Technology at Deep Genomics have?

The Head of Platform Technology at Deep Genomics has diverse responsibilities, including building a team dedicated to advancing NGS, genomics, and molecular biology capabilities. This position involves collaborating cross-functionally to design innovative strategies that unlock new genetic medicines, developing large-scale multi-omics data generation projects, and mentoring scientists to foster a culture of high-quality data generation.

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What qualifications are required for the Head of Platform Technology role at Deep Genomics?

To qualify for the Head of Platform Technology position at Deep Genomics, candidates should have a PhD in biological sciences, along with 15+ years of post-graduate experience in relevant genomics technology roles. Additionally, a strong background in leading teams and developing high-quality assays in advanced data environments is essential.

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How does Deep Genomics support career growth for the Head of Platform Technology?

Deep Genomics offers exceptional growth opportunities for professionals in the Head of Platform Technology role, including access to innovative projects at the intersection of AI and biotechnology, a supportive work environment, and mentorship from industry leaders. Additionally, a competitive salary and meaningful equity ownership enhance career development.

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What makes the Head of Platform Technology position at Deep Genomics unique?

The Head of Platform Technology position at Deep Genomics is unique due to its focus on integrating AI with drug discovery, allowing professionals to work on cutting-edge genomic technologies. The role promotes collaboration across a multidisciplinary team and offers the chance to influence both scientific and corporate initiatives.

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What technologies should a Head of Platform Technology be familiar with at Deep Genomics?

The Head of Platform Technology at Deep Genomics should be well-versed in a variety of technologies, including NGS, molecular profiling, gene editing, and high-throughput assays. Familiarity with automation, quantitative modeling, and multi-omics data analysis is also highly beneficial for this role.

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How does Deep Genomics encourage innovation for the Head of Platform Technology role?

Deep Genomics fosters innovation for the Head of Platform Technology role by promoting collaboration across teams, encouraging creative thinking, and maintaining a close feedback loop between modeling and experimental design. The company invests in cutting-edge technologies and tools to inspire scientific exploration.

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What is the work environment like for the Head of Platform Technology at Deep Genomics?

The work environment for the Head of Platform Technology at Deep Genomics is dynamic and collaborative, featuring a collegial atmosphere filled with motivated professionals. Employees work on multidisciplinary teams tackling complex challenges at the forefront of AI and biotechnology, making it an exhilarating place to grow one's career.

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Common Interview Questions for Head of Platform Technology
Can you describe your experience with next-generation sequencing (NGS) technologies?

When addressing your experience with NGS technologies, ensure to detail specific projects you've led or participated in. Discuss the types of platforms used, any challenges faced, and how you overcame them. Highlight your role in data analysis and how the results contributed to advancing drug discovery or understanding genetics.

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How do you approach building a multidisciplinary team?

In answering this question, share your strategy for attracting and nurturing talent from various scientific backgrounds. Emphasize the importance of fostering a collaborative atmosphere, setting clear goals, and aligning team members’ skills with project needs to enhance productivity and innovation.

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What strategies do you implement for data quality assurance in genomic studies?

Discuss the specific protocols you have established for ensuring data integrity, such as validation procedures or automation techniques. Emphasize your experience with feedback loops between experiments and AI model training, ensuring high-quality data generation consistently.

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Could you provide an example of a successful cross-functional project you've led?

Choose a project that showcases your leadership skills and your ability to navigate multiple teams. Explain the project's goal, your responsibilities, how you facilitated collaboration, and the outcomes that were achieved, highlighting the impact on drug discovery or genomic research.

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What technologies and methodologies do you find essential for optimizing genomic data analysis?

Focus on the tools you've used extensively, such as ELN systems or specific bioinformatics platforms. Discuss your ability to integrate various analytical techniques and how these enhance the accuracy of your genomic data analysis, thereby informing subsequent modeling or experimental work.

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How do you stay current with advancements in genomics and AI technologies?

Share your approach to ongoing education, such as attending conferences, participating in webinars, or reading current literature. Explain how you incorporate new knowledge into your work and foster a culture of continuous learning within your team.

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What challenges have you encountered in the integration of AI with drug discovery processes?

Identify specific challenges you faced while integrating AI into drug discovery, such as data compatibility issues or the complexities of model training. Discuss how you addressed these obstacles, showcasing your problem-solving skills and adaptability in a rapidly evolving space.

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Describe your experience with mentoring and developing team members.

Highlight your mentoring approach, including how you evaluate team members' strengths and areas for growth. Provide examples of how you've supported their professional development through training, feedback, or fostering new opportunities within project work.

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How do you envision the future of genetic medicines, and what role would you play?

Articulate your perspective on emerging trends in genetic medicine, integrating your understanding of technology and patient impact. Illustrate how your leadership in the Head of Platform Technology role at Deep Genomics would contribute to this evolving landscape.

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What methods do you find effective for communicating complex data to non-technical stakeholders?

Describe your communication strategy when presenting complex data, focusing on using visual aids, analogies, or simplified language. Emphasize the importance of tailoring your message to diverse audiences, ensuring clarity and understanding while engaging different stakeholder perspectives.

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Full-time, on-site
DATE POSTED
November 28, 2024

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