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: Collaborate with stakeholders and data teams to identify business challenges amenable to machine learning solutions; Perform exploratory data analysis to uncover insights and transform business questions into concrete modeling tasks; Develop, optimize, and enhance machine learning algorithms and neural network architectures for natural language processing, computer vision, forecasting, and other domains; Build reliable end-to-end ML pipelines for data processing, model training, evaluation, and deployment; Continuously monitor, retrain, and update models to maintain predictive accuracy; Operationalize and serve models at scale using containers, orchestration, and cloud infrastructure
Requirements: Have a B.Tech/M.Tech or equivalent in Computer Science, Statistics, Mathematics, or related quantitative field or equivalent experience; Have 8+ years of professional experience developing and deploying machine learning models and pipelines at scale; Self-starter who can take initiative, drive consensus, and mentor junior team members; Strong software engineering skills and experience developing in languages like Python, R, and Scala; Experience with statistical and machine learning theory, algorithms, and frameworks like SciKit-Learn, PyTorch, TensorFlow

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: Learn about Risk Weight Assets calculations and capital requirements; Be involved in Stress RWA analysis/review; Develop and maintain reports and analysis tools focusing on capital charge; Take part in projects focusing on the implementation of new requirements from the regulator or senior management; Create ad hoc analysis and regulatory data requests; every day is different; Understand the portfolios and businesses of the Firm from a risk standpoint; Partner with key business areas and stakeholders to assure compliance with external regulations; to meet the ever-changing regulatory environment
Requirements: Bachelor’s or higher degree in a quantitative field such as Finance, Economics and Mathematics; General financial product and market knowledge; 5+ years of relevant work experience in the financial industry, preferably in risk management, treasury capital management or regulatory reporting

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: Manage model risk across the model lifecycle including model validation, ongoing monitoring and annual reviews; Independent model validation work, providing effective challenge in regards to mathematical formulation, model assumptions and limitations, calibration, implementation, numerical performance, and business uses; Write high-quality model validation documents in compliance with model risk management policy and procedures, internal audio requirements, and regulatory guidance; Manage stakeholder interaction with model developers and business owners during the model lifecycle; Be ready to assist in the bank interactions with Internal Audit and Regulatory Agencies, as required; Contribute to strategic, cross-functional initiatives within the model risk organization
Requirements: Master’s Degree required, preferably in quantitative field (Mathematics, Statistics, Financial Engineering, Quantitative Finance etc.) with 2 years of experience in model validation; Experience in model validation in one or more of Credit Risk, Market Risk or etrading models; A firm understanding of model risk management regulatory guidance SR 11-7 as it relates to effective model validation practices is expected; Sound knowledge of at least one of the following programming languages; Python or R required

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

Duties: Successful candidates will carry out research in the area of Smart European Electricity Markets, making a contribution to a successful energy transition in Luxembourg and the EU. As such, the candidate will also be involved in various (inter-)national initiatives and engage with different (political) decision makers to shape future markets in Europe. Candidates will have the opportunity to investigate a broad range of research areas and design an individual research portfolio with high policy impact. As such, successful candidates will be able to align the skills that they learn pursuing a doctorate with their personal goals and interests
Requirements: Master’s degree in Energy Policy, Energy Economics, Mathematics, Operations Research, or a related field; Strong knowledge of quantitative and/or computational research methods, ideally optimization and simulation models or forecasting/econometric analysis; Proficiency in one of the major programming languages such as Python; A collaborative team player with a desire to make a personal impact within our interdisciplinary research group and our broader economy and society

Duties: Methodological advances enable a deeper characterization of tissues on the cellular (single-cell omics) and spatial level (imaging). Computational methods are needed for data integration and for gaining deeper insights, e.g., into metabolic rewiring in neurodegenerative diseases. In this project we aim to 1. Further develop a computational approach for the integration of single-cell RNA-Seq and imaging data towards the detailed metabolic network modelling of brain tissue on a multi-cell population level. 2. Apply this framework for the deeper characterization of metabolic alterations in neurodegenerative diseases and for the prediction of novel drug candidates and combinations
Requirements: PhD in Systems Biology, Computational Biology, Bioinformatics or equivalent. Strong background in computational and molecular biology, especially data, network and image analysis, as well as in biochemistry

Duties: Impegnarsi nell'integrare le descrizioni qualitative con i modelli quantitativi nell'ambito della pianificazione dei sistemi energetici; Sviluppare e suggerire approcci innovativi per l'analisi e la creazione di modelli relativi alle politiche basate su dati quantitativi; Analizzare molteplici scenari di transizione energetica su scala regionale, considerando i compromessi sociali, l'incertezza e gli effetti di lock-in; Pubblicare i risultati della ricerca su riviste accademiche peer-reviewed e presentare a conferenze pertinenti
Requirements: Laurea specialistica o dottorato in ingegneria, scienze ambientali, statistica applicata, informatica o un campo correlato; Interesse per la modellazione di sistemi multi-energetici, per le politiche basate su modelli e dati, per il processo decisionale in condizioni di incertezza, per il lavoro con dati e statistiche nazionali e regionali in un ambiente multidisciplinare, per gli strumenti visivi per la pianificazione partecipativa

Duties: This postdoctoral position is linked with a research effort aiming to apply cryptographic methods for studying the security aspects of Artificial Intelligence (AI). Cryptographic approaches will be tested for attacks on AI and existing protection methods in cryptography will be applied for security of AI. The candidate will have the freedom to explore new related topics and drive the research in the direction of security of AI and cryptographic elements
Requirements: Applicants must hold a Norwegian PhD or an equivalent degree within cryptography or AI; Applicants should have a genuine interest in AI, and the research proposal must be related to artificial intelligence

Duties: Are you looking for a student job during the school holidays? Are you curious to explore the fascinating and exciting world of research? The Luxembourg Institute of Socio-Economic Research (LISER) might have the right mission for you
Requirements: You are between 15 and 26 years old; You are enrolled on a full time-basis in a Luxembourgish or foreign educational establishment, or have graduated less than 4 months ago; You are fluent in English and speak at least one of the official country languages (French, German or Luxembourgish)

Duties: Conduct cutting-edge research in the field of joint communications and sensing (remote sensing and/or PNT) for the next generation of non-terrestrial networks; Develop innovative solutions and algorithms for integrating communication and sensing capabilities by solving inherent challenges of the space-based or airborne networks; Collaborate with interdisciplinary team of researchers at SIGCOM to identify unexplored areas of potential breakthroughs in the field; Stay abreast of the latest advancements in satellite communication, signal processing, radar technologies, navigation algorithms, and related fields
Requirements: A PhD degree in Telecommunication Engineering, or Electrical Engineering or Computer Science/engineering with a focus on wireless communications; Experience in signal processing for wireless communication algorithms; Proven knowledge of the optimization theory; Good understanding or willingness to learn the radar technologies; Sound publication track record in relevant international conferences and top journals in the related research areas (communications and/or sensing and/or PNT, IEEE Transaction publications are highly recommended); Strong programming skills in MATLAB. Python/TensorFlow or C/C++ are a plus but not mandatory

Duties: The project aim at optimizing the performance of forthcoming 6G networks through the deployment of reconfigurable intelligent surfaces in both low (sub-6 GHz) and high frequency (millimeter-wave and THz) bands. In addition, the candidates are expected to disseminate results through scientific publications and conferences and actively contribute to the preparation of new research proposals to attract industrial, national, and European projects and to the day-to-day supervision of PhD students
Requirements: The candidates are required to be holders of a PhD degree in Telecommunication Engineering or Electrical Engineering with a focus on wireless and mobile communications. The ideal candidates should have a strong background in signal theory, digital communications, and signal processing with focus on a number of the following subjects: Wireless and mobile communications. Background on either satellite or millimeter wave/THz communications is highly desirable; Multiple-antenna transmission and reception methods in fading channels, both narrowband and frequency-selective. Topics of interest are: massive-MIMO, cell-free massive MIMO, hybrid analog-digital beamforming, distributed antenna systems

Duties: Work closely together with other team members; Stay educated on private capital markets and conduct research towards current market developments and long-term trends to derive actional investment ideas; Take responsibility and be a key contributor in the due diligence process for new investments in funds and in bespoke managed account solutions (i.e. manager selection, commercial due diligence, involvement in legal and tax due diligence activities and monitoring); Monitoring of the existing private equity and private debt portfolio
Requirements: University degree in finance, economics, business administration, mathematics, or engineering with a good degree or a banking education with a capital market specific qualification; e.g; CFA or CAIA; Knowledge of the corporate finance toolkit (valuation, LBO, M&A and accounting) with corresponding ability to implement know how in cash flow analysis and investment models

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: Design and develop machine learning systems and run machine learning tests and experiments; Select appropriate datasets, and run machine learning tests and experiments; Perform statistical analysis and fine-tune using test results; Train, monitor and retrain systems when necessary; Bring models to production; Ability to write robust code in Python
Requirements: Master’s degree; Previous Experience in Fintech will be a plus

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