Duration: 1 y
Duties: the research activity is focused on the planning and implementation of experimental tests aimed at studying the reliability of power electronic devices. The analysis is aimed at investigating the degradation mechanisms related to several stress sources, such as thermal/power cycling or shortcircuit current. The experimental study will be used to develop and to calibrate predictive models, based on artificial intelligence techniques, able to estimate the lifetime of components; Analysis of Si-based and Wide Bandgap-based (SiC or GaN) power electronic devices. Implementation of experimental tests in which power devices are subjected to wear-out phenomena. Development of lifetime models for semiconductor devices - Report on degradation mechanisms about advanced electronic devices; ing-inf/01 - elettronica
Requirements: Early stage researcher or 0-4 yrs (Post graduate)

Duties: Responsible for the design and implementation of a global-scale machine learning system for feeds, ads and search ranking models; Responsible for improving use-ability and flexibility of the machine learning infrastructure; Responsible for improving the workflow of model training and serving, data pipelines and resource management for the multi-tenancy machine learning systems; Responsible for designing and developing key components of ML infrastructure and mentoring interns; Support the production of scalable and optimised AI/machine learning (ML) models; Focus on building algorithms for the extraction, transformation and loading of large volumes of realtime, unstructured data to deploy AI/ML solutions from theoretical data science models
Requirements: B. Sc or higher degree in Computer Science or related fields from accredited and reputable institutions; Proficient in C/C++/Python, and have solid programming skills; Familiar with deep learning frameworks (TensorFlow/Pytorch); Experience in developing and deploying large-scale systems

Duties: Serve as a statistical consultant for other members of the department and staff members from other Biostatistics departments within the company. Maintain knowledge and awareness of developments in Biostatistics and clinical trial methodology, and regulatory requirements that impact analyses. Represent clients at meetings with regulatory agencies or other regulatory meetings, may participate as a member of a Data and Safety Monitoring Committee. May participate in independent research activities, teaching opportunities, presentations, and preparation of manuscripts for publication, as approved. May participate as high level lead biostatistician on major project(s) including developing/reviewing protocols, preparing analysis plans, and writing sections of joint clinical/statistical reports, integrated summaries and/or new drug application (NDA) sections, as required. Provide advanced technical expertise for internal and external clients. Assist and contribute to governance structures whe...
Requirements: Bachelor's Degree Biostatistics or related field and 12 years relevant experience including 6 years experience managing staff Req Or; Master's Degree Biostatistics or related field and 12 years relevant experience including 6 years experience managing staff; Typically requires 12+ years relevant experience including 6 years experience managing staff or Equivalent combination of education, training and experience

Duties: Provide a rigorous assessment of the incidence and prevalence of disease targets using literature reviews, database analysis, or extrapolation of estimates; Guide and advise clinical development study teams on the design and collection of natural history data to better understand disease progression including risk factors and optimal endpoints for use in clinical trials; Use real-world and clinical data to refine population size and characteristics for disease targets as clinical development progresses, in both rare disease and prevalent disease areas; Partner with Clinical Research and GPSRM to help interpret and refine potential safety signals during drug development. Understanding of signal evaluation techniques is required
Requirements: Doctoral degree (e.g. PhD, MD, ScD) and/or Master’s degree (e.g. MSc, MPH) in Epidemiology or related discipline, such as Health Services or Pharmaceutical Outcomes Research, with a minimum of 5 years (PhD) or 8+ years (MS) of relevant experience. Preference for a minimum of three (3) years of that experience developing RWE strategies and/or executing epidemiology studies

Duties: To assist the Head of Statistics in providing timely communication to the function; Leadership of members of the statistical function within specific geographical regions; Line manage senior members of staff within the statistics function, allowing individuals the opportunity to reach their full potential; Training and mentoring line managers and less experienced members of staff within the Statistics function; Support resolution of any issues escalated by or involving statistics team members; Support the operational success of studies through careful planning and work assignments; Helping the Head of Statistics identify areas of skill development for the statistics function as a whole; Work closely with cross-functional Operational leadership team
Requirements: Educated to PhD or MSc in Biostatistics or a related discipline; Experience within the pharmaceutical industry to have a good awareness of clinical trial issues, design, and implementation; Familiarity with GCP and regulatory requirements; Experience of writing SAPs, protocols & regulatory submissions

Duties: Represents biostatistics at cross-functional team meetings to drive clinical development of drug candidate and provides input on clinical development plans; Collaborates with Clinical Development, Regulatory and Clinical Operations Expertise Areas to design clinical trials; Writes the statistical sections of clinical trial protocols, while consulting with internal and external experts; Contributes to or prepares statistical analysis plans; Collaborates with Data Management, Clinical Development and Clinical Operations on design of eCRFs; Provides statistical guidance on conduct of ongoing trials; Collaborates with Statistical Programmers on summary and analysis of trial data; Writes ADS and ad hoc analysis specifications
Requirements: Ph.D. in Biostatistics or Statistics or Equivalent with at least 7 years pharmaceutical biostatistics experience; or MS with at least 10 years relevant experience; Excellent written and oral communication and presentation skills; Experience programming in SAS

Duties: Lead the maintenance and enhancement of RGA’s global pricing framework; Coordinate with pricing teams, business units, corporate functions, and leadership to ensure that the pricing framework is a robust, effective tool for making decisions and for implementation of RGA’s strategy; Create, manage, and update global pricing guidelines, and support business units on pricing transactions consistent with the spirit and intent of those guidelines
Requirements: Bachelor’s degree in Math, Finance, Actuarial Sciences, Statistics or related field; Fellowship, Society of Actuaries (FSA) (or equivalent designation with a recognized Actuarial Institute or Society); 15+ years’ experience in life or health insurance and/or reinsurance: includes 5+ years’ experience in life/annuity pricing and/or product development; 7+ years management experience

Duties: The Boeing Korea Engineering and Technology Center (BKETC) is seeking Talented AI/ML Software engineers who will be responsible for Creation of best-in-class models and ensembles that can be re-purposed and reused, covering domains of Classification, Prediction, Fusion, Decision Making, and Generative AI solutions, as part of the AI Factory team at the BTECK Korea site
Requirements: Bachelor, Master or Doctorate of Science degree from an accredited course of study, in AI/ML Engineering, Computer Engineering, Software Engineering, Computer Science, Mathematics, Physics or other technical degree; 5-10 years of experience in developing models and ensembles in the AI/ML space

Duties: Solves unique and complex problems; requires conceptual and innovative thinking and education and/or equivalent experience to develop solutions; Responsible for the delivery of end results focused on operational excellence; Makes decisions guided by function/business plans and policies that impacts the operations of a sub-function or work area within a sub-function
Requirements: Actuary; Experience using Prophet

Duties: Spearhead research initiatives in Machine Learning and Generative AI that lay the groundwork for advancements across a wide range of scientific and technological domains; Collaborate and foster a culture of innovation with a team of world-class researchers and scientists to explore and solve fundamental problems in AI, with a focus on generating impactful, cross-disciplinary applications; Translate theoretical AI concepts into tangible solutions and methodologies that address complex issues within various fields of study and industry sectors
Requirements: An established background in Machine Learning and Generative AI, evidenced by a PhD in a relevant technical field or equivalent experience; A strong portfolio of Machine Learning research projects, demonstrating a history of impactful contributions

Duties: Lead/support the development and enhancement of efficient tool kits and infrastructure for the Actuarial Pricing Function, to enable business critical delivery of Business Plan and Underwriting Risk Parameterisation for the whole of EMEA across all lines of business. Liaise with all Pricing Actuaries and other key stakeholders to ensure tools are fit for purpose. Engage and co-ordinate the support of other functions such as IT, BI and Finance to ensure seamless delivery; Collaborate with multiple stakeholders (pricing actuaries, finance, reinsurance, reserving actuaries, cat modelling team etc) to build the annual plan and strategic plan; Contribute to the success of Chubb by delivering timely, accurate and insightful management reports to the Senior Executive Team
Requirements: Strong numerical and analytical capability. Ability to understand and grasp the nuance of numerical processes quickly, suggest and implement solutions; Practical knowledge of MS Office Suite including VBA macros. Self starter/ability and interest to pick up and work with new technology/applications with ease. Working knowledge of Alteryx, R, SQL, Dataiku is a plus; Good organisation skills and ability to deliver to tight timescales/run with projects independently; Adaptable to change and happy to take on a challenge, comfortable working in a dynamic environment with regular changing requirements

Duties: Manage a diverse portfolio of software and databases, ensuring data integrity and accessibility for ongoing institutional research efforts; Provide computational support for scientific projects, including data processing, analysis, and visualization; Collaborate with cross-functional teams to design, implement, and support novel software tools, web applications, and database systems for scientific data analyses; Develop automated software tools to facilitate generic workflow capabilities of scientific data management and ensure easy access to databases; Work closely with researchers and the core team to define and implement new software tools to support cancer research; Will function as a software engineer working closely with core team members and investigators to define and implement new software tools to support cancer research; Train core staff on the use of tools to interface and query database systems
Requirements: Master's Degree in Computer Science, Computer Engineering, Bioinformatics, or a closely related area; 2+ years of experience in scientific software and large-scale database system design and implementation; Strong proficiency in UNIX/LINUX programming and in at least one of the following programming languages: R, Python, C, C++, PHP, Perl, or Java; Ability to translate business requirements into technical specifications and complex datasets into simple recommendations; Git-based version control experience

Duties: Work closely with other domain experts to refine and execute Dolby’s technical strategy in artificial intelligence and machine learning; Use deep learning to create new solutions and enhance existing applications; Combine domain knowledge with state-of-the-art deep learning techniques that run on a wide range of computing platforms; Works with a general understanding of competitive technologies in the area of focus; Works to understand the system context in which new technologies will be used and the requirements that the technology must fulfill for success; Creates early-stage conceptual models that demonstrate feasibility; Document and present the new architectures and algorithms in various forms, such as technical white papers and internal meeting
Requirements: Ph.D. degree in electrical engineering, computer engineering, or computer science; Minimum of 3 years of experience in developing algorithms for machine learning and deep learning, computer vision, and vision-language model; Intimately familiar with computer graphics, video processing systems, as well as corresponding software in consumer and professional products; Strong theoretical background in AI technologies and a proven ability to apply AI to audio, video, and speech technologies.Proficient in Python (Tensorflow/Pytorch) programming applied to vision language model is required

Duties: The primary aim of this role is to provide a wide range of advanced statistical expertise, guidance, and support to quality improvement (QI) researchers, scientists; faculty, QI teams, and managers engaged in QI projects or QI research studies within Grady Health System (GHS). This position applies comprehensive knowledge of statistics and the scientific method to the development/design, analysis and reporting of healthcare quality and/or research studies. Provides guidance in appropriate study design, sample size, data collection methodology, and analysis methods for any GHS -initiated or collaborative studies. Supports physicians, clinical faculty, administrators, and staff through preparation of statistical analysis plans, detailed statistical analyses of data and written documents needed for reports, presentations and/or peer-reviewed publications. Advises the system as to process, methods or education needed to improve data, analytic processes and quality or research-related activ...
Requirements: Master's Degree in Biostatistics, Statistics, or a related field Preferred: Three (3) or more year’s job related experience including experience with utilizing statistical software such as R, SAS, or SPSS for data analysis and modeling. Assisted in the publication of QI/QI research findings, ensuring statistical soundness

Duties: Provide statistically rigorous expertise including hands on development on study design, statistical analysis plans, communication of statistical results, project development plans, regulatory issues, and scientific and other product support projects; Accountable for timeliness and quality of study/submission level statistical deliverables on assigned projects; Write Statistical Analysis Plans including mock TFLs for studies and cross study integrated analyses; Partner closely with Data Management on eCRF and DB design, data cleaning and activities to support in stream data cleaning, freezing/locking subjects and database lock; Partner closely with Statistical Programming to draft SDTM/ADaM specifications, QC datasets and tables, listings and figures
Requirements: Advanced degree in statistics or biostatistics; PhD preferred; A minimum of 8-12 years of experience in Pharma/Biotech designing phase 1-4 clinical trials, analyzing and reporting clinical trial data; A minimum of 8-12 years of experience in R and SAS programming including R packages, graphics (e.g. waterfall, spider, box plots, forest plots, etc) in a clinical trials setting; A minimum of 6 years of experience in oncology including regulatory submission experience for oncology medicines; Strong technical and statistical expertise including interim analyses, Bayesian approaches, mixed models, survival analysis methods, etc; expertise in statistical software tools, e.g. EAST

Duties: With the continued growth of our market access, health economics and healthcare value demonstration business we are looking to add a talented Data Scientist to our expanding team. You will have a genuine passion for problem solving and generating robust and elegant solutions based on your experience and knowledge in data science/analysis, machine learning and artificial intelligence. You will contribute technical expertise by identifying and supporting solutions that optimise projects to meet the evolving needs of our clients, helping to drive the growth of our technical innovation, to increase efficiency of current services and develop new innovative services to broaden our client offer. Working within the technology and commercialisation team, you will be contributing to the further development of PROVE’s evidence research and review solutions, client service and commercial success
Requirements: University qualification in computer science/data analytics; Experience in machine learning, artificial intelligence, data visualisation; R, Python, use of data visualisation packages e.g. Power BI

Duties: Works collaboratively with Clinical Development staff to meet project deliverables and timelines for statistical data analysis and reporting; Generates or oversees the production of programming deliverables (e.g., tables, listings) for Oncology study reports and integrated summaries; Anticipates resource needs and works with management and HR to ensure adequate long-term resource allocation within an Oncology project; May manage a small team of programmers; Designs and/or codes analysis files; Ensures programming and corresponding documentation is completed in a manner that is consistent with departmental procedures; Is responsible for all programming activities within an Oncology project or equivalent
Requirements: 8 years of experience and a BS degree in Biostatistics/Computer Science or equivalent

Duties: Leverage data to inform strategic directions of safety signal development, aid in incident response, automate detection and enforcement, and provide intelligence on ecosystems; Operationalize and evolve Threat Detections metrics that measure the impact of our targeted enforcement; Provide guidance to the rest of the company on how to ingest our signals to prevent further exposure of harmful content; Disseminate intelligence gathered to other safety stakeholders and executive decision makers
Requirements: 6+ years of data science industry experience; 2+ years of experience in intelligence analysis, skills in threat hunting and information operations is a plus; Proficiency with relational database (SQL), programming (Python or R), statistics, and network analyses

Duties: Program and validate datasets and SDTMs, including complex efficacy, labs, etc; Program complex non efficacy outputs/figures; Develop and debug complex macros; Create, QC and update complex dataset specifications (including efficacy) for single/multiple studies; Review simple study design SAP without supervision; Review all shells without supervision and provide feedback
Requirements: Educated to BSc or above within Computer Science, Mathematics or a Science related discipline; SAS Programming Experience within the pharmaceutical industry; SAS Programming Experience within the pharmaceutical industry; Good awareness of clinical trial issues, design, and implementation

Duties: The biostatistician will work with multidisciplinary teams on the design and analysis of research studies, results summary and interpretation, and manuscript/report preparation. There will be opportunities to work with the faculty members on methods development projects and first-authored manuscripts
Requirements: Masters degree in Biostatistics, Statistics, or a related field with strong quantitative training; Minimum of two years of related experience

Duties: Lead the technical design across the team as needed to build Generative AI tuning and optimization platforms to improve model quality and performance, as well as providing a guide for research innovations to be translated into safe and reliable products; Work with partners from Google Research and Product Areas (e.g., Ads, Search, YouTube, Google Cloud, etc.), to develop Generative AI tuning and optimization tool chains, platforms, and techniques. Influence partners and stakeholders across the organization to build joint roadmaps and drive outcomes for product; Lead, design, and develop the Generative AI Model to Production strategy in alignment with Core ML strategy
Requirements: Bachelor's degree in Computer Science, Mathematics, other relevant engineering field, or equivalent practical experience; 15 years of experience as a Software Engineering leader in ML Infrastructure, ML or AI for products, or related fields; Experience with machine learning systems; Experience motivating others at all levels by creating a roadmap

Duties: Conduct Bioinformatics analyses of bulk and single-cell RNA and TCR sequencing data related to the study of preclinical and clinical TIL products; Aid biological and immunological interpretation of sequencing data; summarize and present results with clear conclusions; Guide wet lab scientists on the design of next-generation sequencing experiments; Develop and implement data analysis pipelines for Next Generation Sequencing and other genomics applications, from raw instrument output to interpretable and publishable results. These include but are not limited to sequence alignment, variant calling differential expression analysis, and single-cell clustering
Requirements: Ph.D. degree in Bioinformatics, Biology, Immunology, Bioengineering or relevant fields with 0-3 years of experience; Fluent in Shell, R, and Python programming. Experience working on a Linux server either locally or on the cloud; Extensive hands-on experience in analyzing next-generation sequencing data on applications including but not limited to single-cell DNA, RNA, and TCR sequencing, whole transcriptome and whole exome sequencing, targeted DNA and RNA sequencing, etc

Duties: Develop targeted, study-specific SDTM and ADaM dataset checks; Perform independent QC, from raw data to ADaM, of primary and key secondary endpoints; Create draft output shells for ad-hoc requests, prepare analysis specs and scope; Deliver programming results for ad-hoc analysis requests; Review outputs provided by CROs for accuracy and consistency with the analysis plan and specs; Review and contribute to the development of study SAP; Collaborate with data management and their programming team to ensure appropriate data collection and reporting; Participate in study team meeting and support statistician operational activities
Requirements: Master’s degree in biostatistics/statistics/public health or similar field; At least 3 years’ experience of statistical programming for clinical trials; Proficiency in SAS, including complex data manipulation, basic analysis procedures, SAS/MACRO, and SAS/GRAPH; Interest in career development as a leading role in statistical programming in pharmaceutical industry

Duties: As Machine Learning and AI Scientist II, you will collaborate in cross-functional teams to design, implement, and continually improve advanced digital vision computational models/pipelines for high-throughput analysis of digital pathology images. You will refine methodologies for data analysis, processing, visualization, and storage. You will strive to maximize efficiency, quality, reliability, and customer usability and satisfaction
Requirements: Ph.D. degree from an accredited institution in Bioinformatics, Biostatistics, Computer vision, or related field; 3+ years of experience in a related scientific discipline (computer vision, machine learning, neural network preferred); Experience in imaging manipulation, machine learning, and neural networks

Duties: Design, develop, and test physiological data collection pipelines including wearable sensors, and sensors of smartphones, smart watches, and EEG glasses; Apply AI and ML methods; Develop digital biomarkers for disease and drug effects; Develop predictive algorithms for prevention of falls and other accidents; Design and develop interactive applications to support patients and caregivers
Requirements: the applicant must hold a master`s degree or equivalent in one of the following disciplines: medical technology, biomedical engineering, computer engineering, computer science, data science, bioinformatics, medicine or similar; competences in machine learning or statistical learning and hands-on experience in data analysis and modelling; hands-on knowledge in building and experimenting with sensor-based systems