Duties: A potential project is to understand the interplay between cell division and cell identity during human development, reprogramming and disease using hESC and organoid models. In this project, some of the specific aims include but are not limited to: To use genome editing technologies to perturb the cell cycle-cell identity cross-talk To measure cell cycle dynamics during cellular transitions by state-of-the-art live cell imaging To integrate sequencing (OMICS) and imaging data sets
Requirements: PhD in areas relevant to Cell, Molecular or Developmental Biology (or in the final stages of PhD submission); Passion for and track record in understanding Gene Regulation and fate decisions; Expertise in sequencing/OMICS approaches (any, including, RNAseq, ATACseq, ChIPseq); Good knowledge of genome editing approaches; Extensive expertise with cell culture

Duties: Participate in the development process of ML based financial products as a technical leader; Collaborate with colleagues on production machine-learning systems and applications; Design, experiment, and evaluate software systems; Write, test, and maintain production-quality code; Represent Bloomberg at conferences and open-source communities; Demonstrate technical leadership by owning cross-team projects; Build the libraries and frameworks that support fault tolerant and testable systems
Requirements: A Degree in Computer Science, Engineering, Mathematics, similar field of study or equivalent work experience; 5+ years of experience building and deploying Machine Learning models to production; 2+ years of experience in leadership, managing and coaching globally distributed teams and influencing third party technology strategy; Extensive experience in software engineering

Duties: We are searching for an outstanding Bioinformatics Engineer with an interest in working closely with computational biologists and experimental biologists to deploy bioinformatic methods and resources relevant to single-cell sequencing and spatial imaging. The focus of this work is the building and maintenance of software tools, pipelines, and resources for integrative analysis of high throughput sequencing and imaging data
Requirements: A PhD degree or equivalent experience in biological sciences, mathematics, physics, bioinformatics, or related discipline with a quantitative background; Knowledge of sequencing and imaging technologies and their application; Proven experience with computational tools and workflows for the analysis of genomic datasets; Strong programming skills and proficiency in scientific computing software and scripting languages such as Python and R

Workload: 100%
Duties: We are seeking two highly motivated and qualified Research Fellows to join Promatix's computational biology group and they will be seconded into the Fisher lab for an initial period. The group investigates the evolutionary dynamics of cancer (initiation, progression, response to therapy and emergence of resistance) using computational models. The post holders will be expected to make significant contributions to the development of computational models for the cancers being studied by Promatix/the Fisher lab (e.g., breast & lung cancer). This will involve data discovery, analysis, computational modelling, and experimental validation in partnership with our experimental collaborators.‍
Requirements: Applicants will have a PhD degree in computational biology, computer science, engineering, physics, mathematics or bioinformatics, or a degree in biological science with substantial experience in computational work. Experience in formal verification methods (in particular, model checking, temporal logic, static analysis, SAT solving and program synthesis), logical modelling and statistical analysis are essential. Candidates should have excellent programming skills in Python, MATLAB, and R. Experience in machine learning and proteomics or other omics is desirable

Duties: Developing and enhance capital modelling capabilities for the Lloyd’s syndicate, SIEL and SEIL, which may involve enhancing parts of existing models for entities, and building/consolidating reports from the models for various uses; Preparing Solvency Capital Requirement (SCR) submissions for Lloyd’s (the Lloyd’s Capital Return) for the syndicate, and supporting other entity model development as required. Communicating results and providing analysis of change to the Head of Capital and Chief Actuary; Supporting annual and ad-hoc parameterisation of capital models. This will involve investigating new methods and seeking new data sources to continually improve the process; Preparing capital metrics and output to aid business planning and management decision making. Communicating these to underwriters to ensure their understanding of key results
Requirements: Qualified/Nearly qualified with Institute & Faculty of Actuaries or equivalent; Strong relevant/technical experience; Reserving principles; Lloyd’s capital setting processes; Solvency II principles, EU directives in relation to Solvency II and capital adequacy

Duties: Conduct research on single-molecule biophysics; Mentoring graduate students in research projects
Requirements: The candidate should have a Ph.D. in physics, biophysics, chemical biology, bioengineering, or a related field

Duties: The Department of Mathematics at the University of Rochester invites applications for several non-tenure track Visiting Assistant Professor positions for new or recent PhDs. The positions are for two years, renewable for a third upon satisfactory performance, and carry a 2-2 annual teaching load. Areas represented by the department, including (1) algebraic topology, (2) analysis, (3) combinatorics, (4) differential geometry and global analysis, (5) number theory, and (6) probability, will be preferred
Requirements: Qualifications include a PhD in mathematics, strong evidence of excellence in the teaching of undergraduates, and outstanding promise in research

Duties: Support global ERM initiatives such as Own Risk and Solvency Assessment (ORSA), internal economic capital modeling, risk appetite & limit framework, catastrophe modeling, and rating agency capital modeling such as AM Best BCAR; Support regulatory solvency and stress test filing in various jurisdictions, in both US and Non-US; Assist capital allocation and Return on Equity attribution by profit center, for both underwriting and investment operations; Provide quarterly reserving analysis using appropriate reserve methodologies and procedures to ensure timely and reasonable recommendations on loss reserves by line and legal entity; Improve reserving data management and reserving tools to enhance efficiency of the reserve review and booking process
Requirements: Bachelor’s degree in Math, Statistics, Finance, Actuarial Science, Accounting, Economics, or other quantitative field. ACAS-FCAS or close to ACAS. 7-12 years of experience in a relevant function (actuarial, enterprise risk management, finance, reinsurance) of the P&C insurance industry. Some P&C loss reserving experience is required. Proficiency in MS Excel is required; programming skills in SQL, VBA, Python, R and other languages is desired. Effective communication and ability to collaborate with different functions across the organization. Knowledge of insurance financials (GAAP, Statutory, IFRS 17) as well as insurance and reinsurance operations is a plus. Knowledge of NAIC ORSA, Solvency II and other global insurance regulatory frameworks is a plus

Duties: The primary responsibility of this role is to increase the systems and data capabilities of the Actuarial team through leading key projects that will arise over time as the needs of the business and actuarial team change. The Development Actuary will also be a key interface between the Actuarial team and IT teams, ensuring that the needs of the team are prioritized and brought to completion. This is a role with dual reporting lines into the Head of Pricing and Head of Reserving, so candidate must be highly skilled in managing multiple stakeholders and progressing multiple projects concurrently
Requirements: Qualified actuary or equivalent; Pricing or Reserving experience; General Insurance background, London market experience preferred but not required; Project work experience; Process improvement experience

Duties: Lead, collaborate, and execute on research that pushes forward the state of the art in 3D computer vision, multimodal reasoning and generative approaches; Directly contribute to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results; Work with the team to help design, setup, and run practical experiments and prototype systems related to large-scale, long-duration sensing and machine reasoning; Contribute to publications and open-sourcing efforts
Requirements: Currently has or is in the process of obtaining a PhD in the field of Computer Vision, Computer Science, Mathematics, a related field, or equivalent practical experience. Degree must be completed prior to joining Meta; Experience communicating research for public audiences of peers; Experience with real world system building and data collection, including design, coding (C++) and evaluation (C++/Python), including experience with modern ML methods and algorithms; Hands-on experience implementing 3D computer vision algorithms and training/evaluating ML and AI models

Duties: Responsible for overseeing the Cyber and Commercial PI products within the Financial Lines portfolio; Rating Models: Maintain, re-calibrate and improve existing rating models. Utilize newly available technology to improve pricing outcomes; Develop additional functionality for exposure, experience and stochastic models; Portfolio Reviews: Perform or review annual profit studies to identify areas of opportunity, and help define the line of business strategy for the upcoming year
Requirements: Nearly/newly qualified actuary; Experience in General Insurance and in particular Financial Lines; Knowledge of programming languages a plus, particularly: SQL, R, or Python

Duties: Oversee teams of Engagement Leads and Deployment Leads who execute day to day customer operations. This includes ensuring customer data is ready for our platform, training new users, identifying insights, escalating and troubleshooting issues, creating value stories, and working with customers; Ensure platform deployments run on schedule and customers understand their data and relevant problems to be solved with the platform; Work closely with senior executive leadership at customer companies to share insights and value stories; Ensure customers are receiving support and guidance on technical issues and that the team is working closely with customer stakeholders to understand their technical requirements and objectives
Requirements: 7+ years as a client/customer-facing project lead, managing teams and working closely with high level executives; 3+ years as a people manager; Leverages problem solving, creativity and technical skills to help organizations use their data to drive impact in the world

Duties: Use Actuarial techniques to analyse a client’s portfolio(s) to provide quantitative and qualitative understanding of the loss exposure and inherent volatility; Assist both reinsurance placements and pitching for new business; Assist with the expansion the Lockton Re analytical toolkit; working with the wider team across the company to provide thought leadership on existing and new methodologies; Build and maintain relationships both internally and externally with clients and markets; Proactively support other senior actuaries and invest in the technical and professional development of analysts across the team
Requirements: FIA preferable; Excellent knowledge of actuarial techniques and methodologies, ideally relating directly to Casualty-specific reinsurance; Ability to clearly communicate methodologies, outputs and limitations internally and externally, to both technical and non-technical audiences

Duties: To support the Head of Pricing, wider team, senior management and underwriting teams in pricing and profitability reviews. This role will also assist in developing the company’s pricing capabilities by taking part to the pricing transformation
Requirements: Nearly/newly qualified of the Institute of Actuaries (or equivalent experience); Pricing experience: building and calibrating pricing tools, individual account case pricings; General Insurance background, London market experience esp. Financial Lines preferred

Duties: Conduct hands on analytics and perform model development procedures independently to support the model development and analytics efforts across customer lifecycle (Acquisitions, Customer Management, Collections). Develop model in compliance with Global Risk and external regulatory guidelines. Explore modeling techniques including new machine learning methods and their application in solving business problems across all account management strategies
Requirements: Bachelor’s degree, or foreign equivalent, in Statistics, Mathematics, Applied Analytics, Economics or a related field, and six (6) years of experience

Duties: Conduct model validation for market risk models (VaR/Stressed VaR/Risks not in VaR/FRTB) by challenging model assumptions, mathematical formulation, and implementation; Conduct independent testing to assess model accuracy and robustness under different scenarios and market conditions; Assess and quantify model risks due to model limitations and develop compensating controls; Develop high-quality validation reports highlighting risks and limitations of models and communicate findings to stakeholders, senior management, and governance committees; Collaborate with Global MRM teams, Model Control Officers, Valuation Control and Risk Managers to manage model risk across the model lifecycle
Requirements: Masters or Ph.D. degree (or equivalent) in Finance, Economics, Mathematics, Physics, Engineering, or a related quantitative field; In-depth knowledge of mathematical finance, derivative pricing, and numerical techniques; The ideal candidate has strong experience with market risk models gained at a financial institution; Experience developing pricing and risk models using Python, R or Excel VBA is a plus

Duties: 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: Recognized as an expert within the company; Anticipates internal and external business challenges and/or regulatory issues; recommends process, product or service improvements; Solves unique and complex problems; requires conceptual and innovative thinking to develop solutions; Adapts function/business strategy plans and policies to address service and/or operational challenges; May play key role in projects, processes or vendor management

Duties: The main aim of the project the post-holder will join is to develop, improve and apply models for improving situational awareness and informing data collection in outbreaks via data analysis and forecasting. Including systematic assessment of the predictive ability of any forecasts made, and whether the inclusion of individual, spatial, behavioural or genetic data can improve them. There is considerable freedom for work within the aims of the project and scope for the development and use of state-of-the-art methodology and computation with direct impact on public health
Requirements: The successful applicant will have a postgraduate degree, ideally a doctoral degree in a quantitative discipline such as epidemiology, mathematics, physics, statistics, bioinformatics or computational biology, or similar research experience. Candidates should have proficient knowledge of a programming language for mathematical or statistical modelling, including some experience with R, and be committed to open research and/or software development. Experience in outbreak analysis or model-based forecasting is an advantage

Duties: The Department of Mathematics and Statistics at Skidmore College invites applications for a full-time Visiting Assistant Professor or Visiting Lecturer for the 2024-25 academic year. This is a one-year position. The position involves teaching 18 contact hours per year, which is typically a 3: 2 course load
Requirements: A doctorate (or ABD status) in statistics, biostatistics, or a closely related field is required for the Visiting Assistant Professor position. A master’s degree in statistics, biostatistics, or a closely related field is required for the Visiting Lecturer position. Preference will be given to candidates with teaching experience. The successful candidate will be able to teach entry-level courses in our statistics curriculum, including our introductory statistics and statistical methods courses

Duties: Develop analytical libraries used for pricing, market analysis and risk-management for Fixed Income Market business. Develop optimization tools for calculating optimal balance sheet, liquidity, and capital charges. Develop web-based front-end interface for stakeholders to view and interact with analytical tools. Create, implement, and support quantitative models for the Fixed Income trading business leveraging a wide variety of mathematical and computer science methods and tools including, mathematical finance, statistics and probability and software engineering. Apply advanced coding skills to code and debug code
Requirements: Requires a Master’s degree, or foreign equivalent in Financial Engineering, Financial Mathematics, Operations Research and Information Engineering, or related quantitative field and 2 years of experience as a Quantitative Analyst, or related position involving quantitative statistical modeling and data analysis for a global financial services institution

Duties: As part of the company's Center for Data Science and Artificial Intelligence (CDSAi) corporate analytics group, applies analytical skills to work on all aspects of the life insurance value chain, ranging from risk models, fraud detection, customer behavior study, process triaging, and marketing prediction to a variety of other analytics solutions. Applies technical data, analytical, and programming skills to ingest, wrangle, and explore external and internal data to create data assets and reports
Requirements: Master's degree in Statistics, Analytics, Computer Science, Mathematics or Machine-Learning (willing to accept foreign education equivalent) and three (3) years of experience performing data analytics and statistical modeling using complex large-sized datasets in the consumer finance domain

Duties: Lead Model Validation activities for the IMM model suite, including prioritization of the Book of Work for the team; Conduct independent testing to assess model accuracy and robustness under different scenarios and market conditions, including, where appropriate the evaluation of developer documentation and testing; Assess, quantify and communicate to stakeholders model risks due to model limitations and compensating controls; Develop and apply high-quality validation standards by conducting independent testing to assess model accuracy and robustness under different market conditions; Highlight risks and limitations of models and communicate findings to stakeholders, senior management, and governance committees
Requirements: Masters or Ph.D. degree (or equivalent) in Finance, Mathematics, Physics, or a related quantitative field; The ideal candidate has strong experience with counterparty credit risk modelling framework gained at a financial institution, including experience facing regulatory requests; The ability to effectively communicate with a wide range of stakeholders (incl. senior management and internal/external auditors), both written and verbally

Duties: Development, enhancement and maintenance of market risk capital forecasting models under stress scenarios to ensure ongoing appropriateness and adaptations to new regulations (e.g. FRTB); Contribution to key regulatory deliverables and programs (e.g. FRTB) as well as analysis and interpretation of key regulatory requirements; Perform ongoing monitoring and evaluation of market risk capital forecasting models, review existing models to ensure they remain fit for purpose and make improvements where necessary; Collaborate closely with the model validation team to understand validation findings and remediate any identified issues
Requirements: MSc or equivalent in a quantitative subject (such as quantitative finance, statistics/mathematics, sciences or engineering); Deep understanding of quantitative risk including good knowledge of financial products and their risk representation; Demonstrable experience in delivering enhancements to risk models; Excellent mathematical, analytical, problem solving and troubleshooting skills

Duties: Develop and optimize scalable ML pipelines to handle large datasets, train intricate models, and seamlessly deploy them into production; Collaborate closely with diverse teams across behavior, perception, research, mapping, and infrastructure to design and implement comprehensive ML solutions; Create frameworks and interfaces to accelerate machine learning development and maximize hardware efficiency; Engineer robust, high-quality software to enhance our vehicles' navigation capabilities and ensure safety on the road
Requirements: Possess a minimum of 4 years of hands-on experience in ML infrastructure or large-scale distributed systems; Demonstrate expertise in ML fundamentals and deep learning frameworks like PyTorch, Jax, Tensorflow, and Keras, with a focus on scalability, optimizations, and profiling; Proficient in Python and experienced in C++ development; Exhibit a strong passion for advancing robotics to improve everyday life experiences

Duties: This Senior Lecturer post is one element of a new and exciting development of our focused research strategy at St George’s following the recent establishment of the Cardiovascular and Genomics Research Institute (CGRI). The appointee will be an active and internationally recognised academic who will support existent areas of research strength in the Institute by addressing at least one area of need where a new Principal Investigator can grow their research group. These areas of focus include: Cardiovascular genomic bioinformatics; Genetic statistics; and Functional genomics and multi-omics
Requirements: BSc and PhD in an appropriate field; Successful track record of at least 3 years of research at a lecturer level