Head of Scientific Automation, Robotics & AI
⚲ Amsterdam / Montreal
About the Role
We are looking for a Head of Scientific Automation, Robotics & AI to lead the transformation of three advanced research laboratories into scalable, data-rich, AI-driven research platforms.
You will work across laboratories focused on ectogenesis, in vitro gametogenesis, and non-invasive BCI. Your mission is to understand how scientific work is done today, identify where automation and AI can meaningfully accelerate discovery, and integrate the systems that make this possible.
This role is about turning complex scientific work into closed-loop experimental systems: experiments should become easier to design, execute, monitor, analyze, and improve through automation, robotics, high-quality data capture, ML models, and AI agents. The long-term goal is to move toward highly autonomous experiments, where scientists define the research direction and hypotheses, while automated systems help plan protocols, operate instruments, collect data, detect failures, analyze results, and suggest next experiments.
You will partner closely with scientific leads. Instead, you will build the technological layer that accelerates their work: lab automation, robotic workflows, instrument integration, LIMS/ELN, data pipelines, experiment tracking, ML models, active learning systems, digital twins, and AI agents for scientific operations.
The ideal candidate is someone who can walk into a frontier research environment, understand both the scientific ambition and the practical bottlenecks, and turn them into an executable automation and AI roadmap.
About the Team
e184 is building technologies to overcome the limits of human biology in reproduction, the genome, and cognition. The team operates across frontier research programs including in vitro gametogenesis, ectogenesis, genome engineering, and non-invasive brain–computer interfaces.
The team brings together scientists, embryologists, engineers, physicists, bioinformaticians, materials scientists, and lab operations specialists working on some of the most ambitious problems in modern biology and neurotechnology. We are building the foundation for autonomous research laboratories — systems where experiments are designed, executed, monitored, analyzed, and improved through a tight loop between scientists, instruments, robotics, software, and models.
You might thrive in this role if you have
5+ experience leading lab automation, robotics, or AI/ML infrastructure in biotech, pharma, life sciences, neurotechnology, or another complex experimental environment.
Strong understanding of wet lab workflows and the ability to work closely with scientists, research associates, lab managers, and engineering teams.
Experience with laboratory automation systems such as liquid handlers, robotic arms, automated imaging, incubators, sensors, assay platforms, or custom instrumentation.
Strong technical understanding of ML applications in experimental science, such as computer vision, time-series analysis, Bayesian optimization, active learning, anomaly detection, or digital twins.
Experience building or integrating LIMS, ELN, data pipelines, experiment tracking systems, or scientific data platforms.
Strong systems thinking: able to connect instruments, protocols, data, models, people, and scientific objectives into one scalable operating model.
Experience hiring, managing, or coordinating multidisciplinary teams across software, hardware, robotics, data, ML, and lab operations.
High tolerance for ambiguity and frontier science: able to create structure where protocols, data formats, and workflows are still evolving.
Proven experience leading quantitative research, trading research, systematic strategy, or data-driven investment teams.
Strong understanding of trading, alpha research, portfolio construction, execution, risk, market microstructure, and the lifecycle of a trading idea from hypothesis to live deployment.
Ability to structure autonomous research units, define their ownership areas, set clear interfaces between teams, and create objective ways to evaluate progress and output.
Strong managerial skills, including hiring, onboarding, mentoring, performance management, compensation input, and resolving conflicts between teams or priorities.
Experience setting research priorities at the portfolio level rather than micromanaging individual tasks.
Ability to design dashboards, metrics, review rituals, and decision-making processes that make research output visible and comparable across teams.
Strong communication skills and the ability to create alignment between researchers, engineers, data teams, risk, and senior stakeholders.
Head of Scientific Automation, Robotics & AI
⚲ Amsterdam / Montreal
About the Role
We are looking for a Head of Scientific Automation, Robotics & AI to lead the transformation of three advanced research laboratories into scalable, data-rich, AI-driven research platforms.
You will work across laboratories focused on ectogenesis, in vitro gametogenesis, and non-invasive BCI. Your mission is to understand how scientific work is done today, identify where automation and AI can meaningfully accelerate discovery, and integrate the systems that make this possible.
This role is about turning complex scientific work into closed-loop experimental systems: experiments should become easier to design, execute, monitor, analyze, and improve through automation, robotics, high-quality data capture, ML models, and AI agents. The long-term goal is to move toward highly autonomous experiments, where scientists define the research direction and hypotheses, while automated systems help plan protocols, operate instruments, collect data, detect failures, analyze results, and suggest next experiments.
You will partner closely with scientific leads. Instead, you will build the technological layer that accelerates their work: lab automation, robotic workflows, instrument integration, LIMS/ELN, data pipelines, experiment tracking, ML models, active learning systems, digital twins, and AI agents for scientific operations.
The ideal candidate is someone who can walk into a frontier research environment, understand both the scientific ambition and the practical bottlenecks, and turn them into an executable automation and AI roadmap.
About the Team
e184 is building technologies to overcome the limits of human biology in reproduction, the genome, and cognition. The team operates across frontier research programs including in vitro gametogenesis, ectogenesis, genome engineering, and non-invasive brain–computer interfaces.
The team brings together scientists, embryologists, engineers, physicists, bioinformaticians, materials scientists, and lab operations specialists working on some of the most ambitious problems in modern biology and neurotechnology. We are building the foundation for autonomous research laboratories — systems where experiments are designed, executed, monitored, analyzed, and improved through a tight loop between scientists, instruments, robotics, software, and models.
You might thrive in this role if you have
5+ experience leading lab automation, robotics, or AI/ML infrastructure in biotech, pharma, life sciences, neurotechnology, or another complex experimental environment.
Strong understanding of wet lab workflows and the ability to work closely with scientists, research associates, lab managers, and engineering teams.
Experience with laboratory automation systems such as liquid handlers, robotic arms, automated imaging, incubators, sensors, assay platforms, or custom instrumentation.
Strong technical understanding of ML applications in experimental science, such as computer vision, time-series analysis, Bayesian optimization, active learning, anomaly detection, or digital twins.
Experience building or integrating LIMS, ELN, data pipelines, experiment tracking systems, or scientific data platforms.
Strong systems thinking: able to connect instruments, protocols, data, models, people, and scientific objectives into one scalable operating model.
Experience hiring, managing, or coordinating multidisciplinary teams across software, hardware, robotics, data, ML, and lab operations.
High tolerance for ambiguity and frontier science: able to create structure where protocols, data formats, and workflows are still evolving.
Proven experience leading quantitative research, trading research, systematic strategy, or data-driven investment teams.
Strong understanding of trading, alpha research, portfolio construction, execution, risk, market microstructure, and the lifecycle of a trading idea from hypothesis to live deployment.
Ability to structure autonomous research units, define their ownership areas, set clear interfaces between teams, and create objective ways to evaluate progress and output.
Strong managerial skills, including hiring, onboarding, mentoring, performance management, compensation input, and resolving conflicts between teams or priorities.
Experience setting research priorities at the portfolio level rather than micromanaging individual tasks.
Ability to design dashboards, metrics, review rituals, and decision-making processes that make research output visible and comparable across teams.
Strong communication skills and the ability to create alignment between researchers, engineers, data teams, risk, and senior stakeholders.
Head of Scientific Automation, Robotics & AI
⚲ Amsterdam / Montreal
About the Role
We are looking for a Head of Scientific Automation, Robotics & AI to lead the transformation of three advanced research laboratories into scalable, data-rich, AI-driven research platforms.
You will work across laboratories focused on ectogenesis, in vitro gametogenesis, and non-invasive BCI. Your mission is to understand how scientific work is done today, identify where automation and AI can meaningfully accelerate discovery, and integrate the systems that make this possible.
This role is about turning complex scientific work into closed-loop experimental systems: experiments should become easier to design, execute, monitor, analyze, and improve through automation, robotics, high-quality data capture, ML models, and AI agents. The long-term goal is to move toward highly autonomous experiments, where scientists define the research direction and hypotheses, while automated systems help plan protocols, operate instruments, collect data, detect failures, analyze results, and suggest next experiments.
You will partner closely with scientific leads. Instead, you will build the technological layer that accelerates their work: lab automation, robotic workflows, instrument integration, LIMS/ELN, data pipelines, experiment tracking, ML models, active learning systems, digital twins, and AI agents for scientific operations.
The ideal candidate is someone who can walk into a frontier research environment, understand both the scientific ambition and the practical bottlenecks, and turn them into an executable automation and AI roadmap.
About the Team
e184 is building technologies to overcome the limits of human biology in reproduction, the genome, and cognition. The team operates across frontier research programs including in vitro gametogenesis, ectogenesis, genome engineering, and non-invasive brain–computer interfaces.
The team brings together scientists, embryologists, engineers, physicists, bioinformaticians, materials scientists, and lab operations specialists working on some of the most ambitious problems in modern biology and neurotechnology. We are building the foundation for autonomous research laboratories — systems where experiments are designed, executed, monitored, analyzed, and improved through a tight loop between scientists, instruments, robotics, software, and models.
You might thrive in this role if you have
5+ experience leading lab automation, robotics, or AI/ML infrastructure in biotech, pharma, life sciences, neurotechnology, or another complex experimental environment.
Strong understanding of wet lab workflows and the ability to work closely with scientists, research associates, lab managers, and engineering teams.
Experience with laboratory automation systems such as liquid handlers, robotic arms, automated imaging, incubators, sensors, assay platforms, or custom instrumentation.
Strong technical understanding of ML applications in experimental science, such as computer vision, time-series analysis, Bayesian optimization, active learning, anomaly detection, or digital twins.
Experience building or integrating LIMS, ELN, data pipelines, experiment tracking systems, or scientific data platforms.
Strong systems thinking: able to connect instruments, protocols, data, models, people, and scientific objectives into one scalable operating model.
Experience hiring, managing, or coordinating multidisciplinary teams across software, hardware, robotics, data, ML, and lab operations.
High tolerance for ambiguity and frontier science: able to create structure where protocols, data formats, and workflows are still evolving.
Proven experience leading quantitative research, trading research, systematic strategy, or data-driven investment teams.
Strong understanding of trading, alpha research, portfolio construction, execution, risk, market microstructure, and the lifecycle of a trading idea from hypothesis to live deployment.
Ability to structure autonomous research units, define their ownership areas, set clear interfaces between teams, and create objective ways to evaluate progress and output.
Strong managerial skills, including hiring, onboarding, mentoring, performance management, compensation input, and resolving conflicts between teams or priorities.
Experience setting research priorities at the portfolio level rather than micromanaging individual tasks.
Ability to design dashboards, metrics, review rituals, and decision-making processes that make research output visible and comparable across teams.
Strong communication skills and the ability to create alignment between researchers, engineers, data teams, risk, and senior stakeholders.
