Duties: Devise, implement and lead research projects focused on identifying and characterizing molecular networks underlying human traits using data from human biobanks and other sources; Use statistical associations, causal inference methods and biological knowledge to generate hypotheses and design experiments to test them; Work in close collaboration with an interdisciplinary group of experimental scientists, computational biologists and statisticians
Requirements: A PhD degree in biology, genetics, computer science, statistics or related fields; 5+ years of experience in statistical genetics and/or epidemiology (including PhD). Post-graduate experience (post-doc or industry) is a plus; Strong coding skills in Python and/or R

Duties: We are seeking a highly skilled and experienced Actuarial Valuation Leader to join our team. The Actuarial Valuation Leader will play a pivotal role in ensuring the accuracy and integrity of our annuity valuation processes, providing valuable insights to support strategic business initiatives and regulatory compliance
Requirements: Fellow Society of Actuaries; 10 years’ experience in actuarial roles within life insurance industry; Technical proficiency in actuarial software (AXIS preferred) and familiarity with data programming languages used in data analysis (e.g., R/Python); Thorough understanding of actuarial principles, annuity products, US Stat, and US GAAP

Duties: Design, develop, and implement state-of-the-art motion planning and trajectory control algorithms to optimize robot paths and ensure precise movement in complex, indoor environments for a multi-robot navigation system; Collaborate with cross-functional engineering teams to seamlessly integrate planning and control algorithms into robotic systems; Conduct rigorous testing, simulation, and troubleshooting to validate performance and identify areas for continuous enhancement and adaptation of the multi-robot system; Identify and implement performance improvements in a large distributed robotic system, leveraging architectural changes as needed; Provide live deployment support and troubleshoot issues in real-time for a fleet of hundreds of robots
Requirements: Master's degree in computer science or similar engineering degree; 5+ years of experience developing production software with C++ or other object-oriented languages; 5+ years experience with techniques and applications in mobile robot controls, path planning, or scheduling/optimization; 5+ Extensive experience debugging and profiling applications/algorithms; Proficiency with working in a Linux development environment

Duties: Shape, grow, and lead exceptional teams that deliver novel, strategic ML solutions for Rokts product offerings; Leverage your ML industry expertise to introduce new technologies and processes and drive innovation within Rokt’s product offerings; Lead the development and deployment of machine learning models for content. understanding, embeddings, recommender systems, and ranking; Develop and maintain a deep understanding of user behavior, preferences, and engagement patterns through the use of ML; Collaborate with cross-functional teams including product, engineering, design, and data science to identify and prioritize opportunities for machine learning; Provide technical leadership and mentorship to the machine learning team; Partner with business stakeholders to understand their needs and develop solutions that drive business outcomes
Requirements: You have a deep technical background in applied machine learning, including deep learning, computer vision, natural language processing, and data engineering; An eye for product and relentlessly putting the customer at the heart of your strategic decisions; Previous experience in building and leading ML teams in creating end-to-end machine learning pipelines, including algorithms and tooling; Nice-to-have: A published researcher with a strong track record of academic experience in ML and AI

Duties: Collaborate with scientists to understand business objectives, product requirements and develop ML algorithms that achieve them; Design and implement production ML pipelines; Deploy ML pipelines and models to production systems and operate them including monitoring and troubleshooting
Requirements: 4+ years of non-internship professional software development experience; 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience; Experience programming with at least one software programming language

Duties: Builds and leads a generative AI practice within CDSAi. This includes use case development and associated stakeholder management in various business areas. It also means talent development (both recruiting new talent and training existing data scientists), infrastructure and tooling (in collaboration with ML Ops and IT), education of stakeholders and community, vendor selection/collaboration and governance (in collaboration with model governance team and Legal); Managing various stakeholders during solution design and project execution to successfully create solutions and deploy them into full production. Organizational effectiveness (within a complex company like NYL), storytelling and product branding are as important as technical leadership; Utilizes advanced statistical/AI techniques to create high-performing predictive models and other solutions to address business objectives and client needs. Tests new statistical and machine learning analysis methods, software, and data sources ...
Requirements: Graduate-level degree with concentration in a quantitative discipline such as statistics, computer science, mathematics, economics, or similar; 8+ years of experience with predictive analytics using large and complex datasets; Substantial expertise in both parametric statistical modeling techniques (linear regression, GLM, survival analysis, time series, etc.) and non-parametric techniques (GBM, NN, NLP); Expertise in regularization techniques (Ridge, Lasso, elastic nets), variable selection techniques, feature creation (transformation, binning, high level categorical reduction, etc.), validation (holdouts, CV, bootstrap) and model performance measures (may need to create new ones)

Duties: Design, create, and manage database systems that allow biologists to investigate data independently; Automate workflows for data retrieval or storage in electronic lab notebooks (ELNs), such as Benchling; Collaborate with a team of scientists to help automate data analysis pipelines and build data infrastructure; Define, contribute to, and proactively communicate data engineering standards and practices establishing repeatable templates and frameworks and efficient usage of cloud services and tools; Communicate insights and progress to the scientific team and executive management
Requirements: B.S. or M.S. in computer science or related field and 3+ years of industry experience; Extensive experience with database technologies, architecture, and management; NGS database development experience with virology, pathology, molecular biology, or similar datasets; Programming experience in scripting languages such as Python, R, SQL, and version control tools; Understanding of ideating and creating UI design deliverables; Working knowledge of AWS services, including EC2, S3, RDS, FSx Lustre, Athena, Glue, Lambda, Batch

Duties: Lead computational investigations into the impact of novel formulations on biology. Partner with cross-functional teams to develop principled design of experiment strategies (e.g., adaptive designs, optimal designs), statistical models and computational methods; Design and carry out data analysis strategies (normalization, statistical inference) for biophysical measurements and bioassays (e.g., ELISA, amplicon-seq, mass spec); Explore and build novel statistical models or machine learning methods to advance our platform technology; Collaborate with bioinformatic engineers and develop tools to enable data democratization; Independently manage multiple concurrent, fast-paced projects across Moderna’s research ecosystem. Partner with wet-lab and dry-lab scientists
Requirements: Ph.D. in Statistics, Biostatistics, or related quantitative discipline; 5+ years of relevant academia or industry experience (post PhD) is required; Establish records working with cross-functional teams (e.g., publications, work experiences); Strong coding skills with R and Python

Duties: Conduct comprehensive telco data analysis for trends and patterns; Collaborate with teams to translate insights into actionable strategies; Design and implement advanced analytics models using ML and statistical techniques; Develop real-time dashboards and reports for informed decision-making
Requirements: Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or related field; 5+ years in telecom data analysis or related roles; Strong proficiency in SQL, Python, or R; Experience with data visualization tools (Tableau, Power BI)

Duties: Translate research ideas into correct, robust, and scalable high-quality code; Engage in programming language design/implementation; Performance engineering, scaling research code; Algorithm development; Contribute to the culture and direction of Basis
Requirements: A PhD (or equivalent experience) in technical areas including: statistics, programming languages, machine learning, computational neuroscience, cognitive science, physics, mathematics. Possess excellent programming and software engineering skills, especially in Julia, Python, C++, ML-family languages

Workload: 100%
Duties: Analyze datasets and develop solutions to business problems using machine learning and statistical techniques; Create impact by solving difficult data science problems using a variety of ML techniques with careful investigations into accuracy/performance; Synthesize analytical and statistical approaches into easy-to-consume storylines, both visually and verbally, and clearly communicate with both non-data science audiences and data scientists; Work closely with the wider data science team to implement best practices and maintain high-quality output
Requirements: M.S. or Ph.D. degree in Mathematics, Machine Learning, Engineering, Physics or other quantitative fields preferred; At least 4 years of experience in an industry setting; Knowledge of underlying mathematical foundations of statistics, machine learning, optimization and analytics; Experience building and using state of the art models such as deep learning in NLP or computer vision or similar application; Excellent verbal and written communications skills; Experienced in Python and SQL

Duties: Leader in bringing innovative statistical thinking and methods to help drive applications of suit-for-purpose statistical methods that enhance the probability of successes for clinical development programs; Collaborate with internal and external stakeholders to ensure effective quantitative approaches are applied to the collection and analysis of a wide variety of data types; Develop statistical sections of clinical development plans, protocols, statistical analysis plans, and key specifications for statistical programming implementation of analyses; Plan, manage, and track biostatistics activities, timelines, and resources and assure operational excellence
Requirements: PhD in statistics (or equivalent degree) with 6+ years or master with 9+ years of relevant working experience in Biotech, Pharma, Regulatory agencies, or Clinical Research Organizations; Excellent statistical knowledge with the ability of applying the knowledge to solve scientific and clinical problems; Working knowledge of relevant ICH guidelines, US, EU and other regions’ regulations; Experience working on oncology, vaccine/infectious disease and rare disease clinical studies and regulatory interactions are preferred

Duties: Building scalable machine learning pipelines, including efficient parallelization and use of GPUs; Designing and coding data processing pipelines, ownership of company-wide data platform; Working closely with Platform Development and Biology teams to automate a tight design-build-test cycle for ML generated small molecules; Working in a collaborative CI/CD software development environment, including use of git, participating in code reviews, and independent development of robust code; Working within an entrepreneurial, collaborative, and interdisciplinary team to actively contribute to creating, shaping, and executing the vision of the company
Requirements: Undergraduate or Master's degree in bioinformatics, computer science, mathematics, physics or related field and 4+ years of experience is required; Experience with MLOps practices and tools including version control, automated testing, and CI/CD; Proficient in Python and experience in using deep learning libraries (i.e. PyTorch); Experience with cloud computing (i.e. AWS), database scale-out (e.g. distributed postgresql), and data pipelining tools (i.e. Nextflow, Airflow); Experience with Slurm or other on-site HPC cluster solutions

Duties: Architect, develop, test, maintain Bioinformatics Pipeline Systems; Research and develop new algorithms, programs to support and improve Bioinformatics system efficiency; Data management, data maintenance and database administration; Identify, design, and implement process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalabilities; Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics; Support business operations, processing, and exceptions; Database design, analysis, implementation, and support; System administration and maintenance
Requirements: A Bachelors Degree with a major in Bioinformatics, Computer Science, or a related discipline; Knowledge of Java, JavaScript, Python, Bash Scripts; Knowledge of Database, SQL; Knowledge of GIT Source Control, Windows, and Linux

Workload: 100%
Duties: The Mathematical Imaging and Visual computing group, part of the Institute for Health Equity Research (IHER) and the College of Agriculture, Science and Technology (CAST), is recruiting a qualified post-doctoral fellow to perform research in the areas of biomedical image analysis and machine learning. The successful candidate must have background in image processing/analysis, machine/deep learning, and data science. The post-doctoral researcher will work on deep learning techniques for image segmentation, image registration, and prediction modeling
Requirements: PhD (required) in Computer Science, Computational Mathematics, Engineering, or related areas; familiarity with medical imaging database management and/or web-based application development

Duties: Apply state-of-the-art machine learning software solutions for various artificial intelligent system applications; Interact with team members to discuss technical solutions to problems; Develop tools and techniques to improve our team's research and development capability; Interact with clients (and potential clients) to discuss and propose technical solutions to unique problems
Requirements: Requires a Bachelors, Masters, or a PhD in Data Science, Computer Science, Computer Engineering, Electrical Engineering, Mechanical Engineering, or related field Classes, projects, or training in perception (computer vision/image processing, LIDAR and/or radar) software solutions for various intelligent system applications Classes, projects, or training in C++, python, and ROS experience required

Duties: Apply state-of-the-art machine learning solutions for various artificial intelligent applications; Interact with team members to discussion technical solutions to problems; Manage the various aspects of a project (e.g., technical goals, team tasking, project budget, reporting); Interact with clients (and potential clients) to discuss and propose technical solutions to unique problems, both in-person and virtually
Requirements: Requires a Bachelors, Masters, or a PhD in Data Science, Artificial Intelligence, Computer Science, Cognitive Science, Computer Engineering, or directly related engineering or related program; PhD with 6 years experience (academic or industry) in machine learning software solutions for various applications such as image processing, ontology, medical data analysis, or mobile robotics

Duties: Act as the data and statistical leader across a variety of research projects; Prioritize and extract data from a variety of sources such as notes, survey results, medical data, and other big data sources, determine and maintain its accuracy and completeness; Determine additional data collection and reporting requirements; Design and customize analytical reports based upon data in the database. Oversee and monitor regulatory compliance for utilization of the data; Use system reports and analyses to identify potentially problematic data, make corrections, and eliminate root cause for data problems or justify solutions to be implemented by others
Requirements: Bachelor’s degree and three years of relevant experience or combination of education and relevant experience. An advanced degree (Master’s or PhD) is highly desired; Experience in a quantitative discipline such as economics, finance, statistics, political science, computer science, engineering, health economics, or biostatistics; Excellent writing and analytical skills; Mastery of R; Knowledge of causal inference methods

Duties: Collect, manage and clean datasets; Employ new and existing tools to interpret, analyze, and visualize multivariate relationships in data; Create databases and reports, develop algorithms and statistical models, and perform statistical analyses appropriate to data and reporting requirements; Use system reports and analyses to identify potentially problematic data, make corrections, and determine root cause for data problems from input errors or inadequate field edits, and suggest possible solutions; Develop reports, charts, graphs and tables for use by investigators and for publication and presentation
Requirements: Bachelor's degree or a combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering

Duties: The School of Engineering and Technology (SET) at the University of Washington Tacoma (UWT) is seeking to hire a postdoctoral fellow in bioinformatics. This full-time position is expected to work with biomedical collaborators to develop analytical workflows, methods and software tools to analyze biomedical data
Requirements: Completed PhD or foreign equivalent in computational or biomedical sciences; At least 1 year of research experience in bioinformatics or related disciplines; Proficient in programming such as Python, R, bash, or shell scripts; Experience writing and publishing manuscript(s) that report original research; Excellent written and oral communication skills required; Ability to work both independently and in collaboration with a team

Duties: Applications are invited for one or more non-tenure-track postdoctoral positions. The initial appointment is for a period of twelve months, full-time, with the possibility of renewal for a total period of up to three years, to begin in September 2023. Duties include engaging in ongoing and active independent research and teaching a full-time load of undergraduate and graduate courses. In particular, the job title will be “50% postdoctoral scholar, 50% teaching associate, ” to reflect these two components of the job
Requirements: Applicants are required to have a PhD, or foreign equivalent, by the starting date, and to be highly qualified to teach a full-time load of undergraduate and graduate courses while also engaging in ongoing and active independent research

Duties: Lead a team that is trying to redefine personalized preventive and regenerative medicine; Apply cutting-edge machine learning, data science and biostatistical techniques to detect human age-related diseases as early as possible; Use your creativity to solve challenging problems
Requirements: We're hiring a Senior Data Scientist with expertise in machine learning and predictive statistics (analytics and modeling). Because you will be working with medical and biological datasets, some background in biomedical sciences is ideal. A deep background in Bayesian methods is highly desirable, as is fluency in R.‍

Duties: At Moffitt Cancer Center, we come face-to-face with cancer every day, but we also see courage. And it inspires us to be the safest and best place for cancer care; to bring greater hope to every patient we serve
Requirements: 5 years of experience with Master's Degree or 2 years of experience with PhD in bioinformatics with prior experience in the processing and analysis of next generation DNA sequencing, microarray, comparative genomics, or other high-volume genomics data is required

Duties: Collaborate closely with product managers and other engineers to understand business priorities, frame machine learning problems, architect machine learning solutions; Build and productionize machine learning models including data preparation/processing pipelines, machine learning orchestrations, improvements of services performance and reliability and etc; Contribute and maintain the high quality of code base with tests that provide a high level of functional coverage as well as non-functional aspects with load testing, unit testing, integration testing, etc
Requirements: Bachelor’s degree in Computer Science, a similar technical field of study or equivalent practical experience. A PhD degree in Machine Learning or Deep Learning is a massive plus; 3+ years of industry experience in building production-grade machine learning systems with all aspects of model training, tuning, deploying, serving and monitoring. Industry Experience in applied ML in Ads is a massive plus

Duties: We are seeking a Principal Data Scientist to enhance our strategic execution by employing advanced data science methodologies in experimental analysis, predictive modeling, and machine learning to solve complex business-case based operational challenges and optimize processes
Requirements: 5+ years of data science experience solving operational issues using advanced statistical techniques and machine learning; Proven solid skills in statistical programming and data manipulation (Python, R), and complex database queries (SQL); Proven ability to effectively communicate complex data science concepts to non-technical audiences