• Own and evolve the Python optimization service that powers the Scheduling Agent, modeling, solving, and iterating on the constraint formulation as new use cases emerge. • Design and implement increasingly sophisticated scheduling capabilities: trade and crew constraints, irregular capacity patterns, production downtime windows, multi-site considerations, and reactive re-scheduling. • Build and maintain API routes and tools that expose the solver to GenAI agent workflows (tool calling, structured input/output). • Partner with PM and design to translate messy real-world scheduling problems into solver constraints, and push back when "optimal" isn't what users actually want. • Iterate the solver with real users via design partnerships and pilot deployments. Take feedback from human schedulers seriously and reflect it back into the model. • Contribute to the surrounding Python service: performance, observability, testing, and reliability of the optimization runtime. • Help shape how scheduling intelligence integrates with the broader MaintainX product over time, including learning from execution data to improve solver inputs.

Role Description The mission of MongoDB Research is to advance the state of the art in database systems by conducting fundamental and applied research that directly impacts MongoDB's products. Our goal is to foster innovation that benefits MongoDB by addressing critical challenges in data management, performance optimization, security, scalability, and usability. We seek an exceptional researcher specializing in database systems with particular expertise in database architecture, including query optimization, storage engines, indexing, and multicore processing. The ideal candidate will demonstrate a strong track record in designing and implementing highly performant database systems. This role can be in-office, flexible, or based remotely in North America. - Conduct innovative research in query optimization, indexing methods, storage engines, and performance optimization - Design, prototype, and empirically evaluate novel database systems and architectures that leverage modern hardware features, such as SIMD parallelism, GPU acceleration, and multicore processing - Collaborate closely with our Engineering teams to translate cutting-edge research into practical solutions applicable in commercial database products - Publish influential research outcomes in top-tier database and systems conferences and journals (e.g., VLDB, SIGMOD) - Build a Database Systems research group with a critical mass of 2-3 researchers over the next 1-2 years - Mentor junior researchers, fostering a collaborative and productive research environment Qualifications - Ph.D. in Computer Science, Computer Engineering, or a closely related field with a specialization in database systems - 12+ years of experience applying computer science concepts to large scale software development problems, including databases and distributed systems - Proven track record of impactful research publications in top-tier database and systems conferences and journals - Demonstrated expertise in query optimization, efficient data structures, and high-performance database architectures - Strong background in performance engineering, hardware-aware optimizations, and database engine internals - Experience in building research prototypes and conducting rigorous empirical studies to validate theoretical models - Excellent analytical, communication, and interpersonal skills, with the ability to collaborate across teams Requirements - Within the first three months, you will have established working relationships with key stakeholders across Product and Engineering - Within the first six months, you will have completed a review of the company’s database roadmap and identified opportunities for research impact. You will have established a clear research agenda for the team - Within the first twelve months, you will have successfully attracted and interviewed researchers to join the team Benefits - Equity - Participation in the employee stock purchase program - Flexible paid time off - 20 weeks fully-paid gender-neutral parental leave - Fertility and adoption assistance - 401(k) plan - Mental health counseling - Access to transgender-inclusive health insurance coverage - Health benefits offerings Company Description MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software. Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter. MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. MongoDB’s base salary range for this role in the U.S. is: $168,000 — $330,000 USD

Role Description Pivot Path Solutions is seeking a Cardiovascular Research Scientist / Physiologist to support advanced research and development efforts in digital twin technologies for predictive medicine. This role will focus on developing and validating physiology-based models of the cardiovascular system, integrating clinical data with computational methods to simulate disease progression and treatment outcomes. The ideal candidate brings deep expertise in cardiovascular physiology, hemodynamics, and computational modeling, with the ability to translate biological systems into predictive, data-driven models. This position will play a critical role in supporting high-impact R&D initiatives aligned with federal research programs. This is a remote position. Qualifications - PhD in Biomedical Engineering, Physiology, Cardiovascular Science, Computational Biology or related field - Strong background in cardiovascular physiology and hemodynamics - Demonstrated ability to work with multimodal biomedical data - Experience with peer-reviewed publications or funded research projects Requirements - Develop high-fidelity physiological models of the cardiovascular system, including blood flow dynamics, cardiac function, and systemic responses - Translate clinical and experimental data (e.g., imaging, vitals, lab values) into computational models - Support the design of digital twin architectures for patient-specific modeling - Build and validate mechanistic (physics-based) models of: - Hemorrhage and shock (acute conditions) - Heart failure and chronic cardiovascular disease - Collaborate on the development of reduced-order models (ROMs) for real-time simulation - Conduct sensitivity analysis, uncertainty quantification, and model calibration - Collaborate with clinicians to ensure biological and clinical relevance of models - Support development of validation strategies, including comparison against human or animal data - Contribute to study design and experimental protocols as needed Benefits - Collaborate on high-impact federal innovation programs - Flexible, entrepreneurial engagement model - Opportunity to shape next-generation digital twin initiatives in mission-critical environments - Direct access to executive leadership and capture strategy discussions

• Apply computational sciences to drug development workflows • Promote computational sciences in drug discovery initiatives • Consult with chemistry and biology experts on scientific data governance • Lead analytical tool development and computational methods development • Collaborate with medicinal chemistry during lead optimization activities • Analyze, interpret, and report research data • Engage in data governance objectives • Ensure compliance with Eurofins policies and practices