Biomedical AI/Machine Learning Postdoc

Ready to join the AQ era?

SandboxAQ is solving challenging problems with AI + Quantum for positive impact. We partner with global leaders in government, academia, and the private sector to identify applications that would benefit from quantum-based applications to current and future commercial challenges. We engage with customers early and throughout the development process to improve market fit.

Our team’s unique approach enables cross-pollination across a diverse range of fields, from physics, computer science, neuroscience, mathematics, cryptography, natural sciences and more! Our success comes from coalescing diverse talent to create an environment where experimental thinking and collaboration yield breakthrough AI + Quantum solutions. Join a culture where thought leadership, diverse talent, employee engagement, and technological impact will create the next tech uproar.

We are deeply committed to education as a means to advance quantum solutions and computing initiatives. We invest in future talent through internship programs, research papers, developer tools, textbooks, educational talks/events and partnerships with universities/talent hubs to attract multi-disciplinary talent. Our hope is to inspire people from all walks of life to be prepared for the quantum era and encourage a path in STEM.

Postdoctoral Fellowships at SandboxAQ

The SandboxAQ Postdoctoral Fellowship is an excellent, paid opportunity for recent graduates to build health-focused, AI-backed products and to learn about the world of industry. All of the teams at SandboxAQ employ Postdoctoral Fellows on a variety of projects, and each have a unique experience depending on the work their team is focused on. Whenever possible, we encourage residents to contribute to patents or publications, attend conferences, build mastery and pursue their professional development. The sensing team emphasizes upskilling in standard software engineering best practices and ML Ops in addition to building AI/ML models, for a complete skill-set that provides fellows a strong future career trajectory. In addition to technical work, community is very important to us and we provide space and events to network and socialize with others in the program, as well as the SandboxAQ community as a whole.

Team Charter

The sensing team develops AI/ML solutions for healthcare, with a near-term focus on cardiac disease. We seek revolutionary impact on human health, by bridging AI/ML, a deep understanding of pathophysiology, product sensibility, dynamic teamwork and business acumen. Fellows will develop and implement novel AI/deep learning algorithms to separate signal from noise and build predictive models. Working closely with a focused team of PhDs, MBAs, engineers, physicians and product experts, you will confront hard social problems, make business impact, and improve lives.

As our newest Machine Learning Fellow, here are some of the things you may work on

As a machine learning resident supporting the sensing team, you will work closely with a cross functional group of machine learning engineers, software and hardware engineers, physicists, physicians, academic partners, product leads and business team experts to build the next generation of AI first tools to impact the development of new medicines. Utilizing your expertise in software engineering, machine learning, and data science, you will:

• Develop deep learning models for cardiovascular prediction problems
• Write high-quality code, aiming toward eventual productization
• Build cross-functional skill-sets in communicating with multiple stakeholders

Qualifications

• Currently enrolled or recently completed a STEM PhD Program in relevant technical field
• Preferred: coursework / qualifying exams are complete
• Proficiency in Python
• Experience developing models using modern machine learning and deep learning frameworks and libraries (e.g. PyTorch, TensorFlow, Scikit-Learn, scipy)
• Experience with a Unix-style terminal environment
• Experience in one or more of the following ML applications applied to a medical or health-related problem: convolutional neural networks, sequence modeling with time series data, transformers and generative AI, reinforcement learning, adversarial learning.
• Experience with signal processing and time series analyses

Nice-to-Have

• Experience working in a cloud environment such as AWS or GCP
• Domain expertise in at least one of the above key areas, as indicated by at least one relevant high-impact publication
• Experience with Transfer Learning, especially in a medical domain

Other Details

• Location: Remote in North America
• Start date: Year-round, on a rolling basis
• Duration: 1-2 years

SandboxAQ welcomes all.