Dauer: 6 m       
Pensum: 100%
Aufgaben: Wirke bei der Konzeption und Entwicklung von Lösungen und Produkten für die Datenanalyse, -berichterstattung und -visualisierung im Bereich Audit und Assurance mit; Erkenne, Erörtere und Untersuche die herausfordernde Geschäftsprobleme von unseren Kund*innen und Wirtschaftsprüfer*innen; Erhalte Einblicke in verschiedene Geschäftsprozesse, IT-Systeme und Datenmodelle unserer nationalen und internationalen Kunden; Unterstütze unser Team bei der Integration unserer Lösungen in bestehende Geschäftsprozesse unserer Kunden; Interagiere mit Kunden verschiedener Branchen und Funktionsbereichen (Marketing, Vertrieb, Betrieb, Finanzen)
Anforderungen: Mindestens zwei abgeschlossene Semester in einer wirtschaftlichen oder technischen Studienrichtung; Grosses Interesse an der Analyse und Bewertung von Geschäftsdaten, IT-Umgebungen und Business-Prozessen; Wille, dir einen fundierten Einblick in die vielfältige Datenwelt unserer nationalen und internationalen Kundschaft zu erarbeiten; Ausgeprägte Eigeninitiative, gute analytische Fähigkeiten mit Anspruch auf höchste Qualitätsstandards; Erste relevante Berufserfahrung von Vorteil; Fliessende Deutsch- und Englischkenntnisse

Aufgaben: 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
Anforderungen: 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

Aufgaben: As a comprehensive university offering a wide range of high-quality educational opportunities, the University of Basel attracts students from Switzerland and the entire world, offering them outstanding studying conditions as they work towards their bachelor’s, master’s or PhD degrees. Today, the University of Basel has around 13000 students from over a hundred nations, including 3000 PhD students. The University of Basel has seven faculties covering a wide spectrum of academic disciplines. In international rankings, the University of Basel is regularly placed among the 100 top universities in the world thanks to its research achievements
Anforderungen: We crawl all higher jobs in research, teaching and administration at Universität Basel automatically and post them at acad.jobs. Additional jobs can be found by clicking here. Many more institutions are listed in the left frame (desktop version), see "Search yourself at 8000 institutions"

Aufgaben: Developing and training machine learning (ML) models capable of accurately reproducing the complex PES of perovskites, including the parts responsible for long-range ion transport; Publication of articles in scientific papers and giving talks at international conferences
Anforderungen: A Ph.D. degree in Data Science and Machine Learning, Physics, or Chemistry; Knowledge of Machine Learning methods and methods of Computational Chemistry; Strong skills in coding and employing HPC facilities; Fluent written and verbal communication skills in English

Aufgaben: Post-quantum security of proof systems; Generalization to Quantum Proof Systems; Participate in teaching tasks and Ph.D. and M.Sc. student supervisions; Collaboration with writing progress reports
Anforderungen: A Ph.D. degree in Computer Science, Mathematics with the focus on Cryptography and its intersection with Quantum Computation & Information; Experience working on computational assumptions, which are believed to be quantum-secure, is a plus; Experience working on quantum-secure proof systems is a plus; Competitive research record in cryptography or Quantum Computation & Information

Aufgaben: Entwicklung und Weiterentwicklung von innovativen Versicherungsprodukten der Lebens- und; Sachsparte mit einem Fokus auf Versicherungsdokumente; Mitarbeit in einem crossfunktionalen, agil arbeitenden Team (ADU), die Aufgabensteuerung erfolgt zeitgemäss durch das Framework SAFe; Zusammenarbeit mit Jurist: innen und weiteren Expert: innen; Aufbau von tiefem Produkt-Know-How, um übergreifende Fragestellungen beantworten zu können und sicherzustellen, dass regulatorische Anforderungen erfüllt werden; Erstellung von Forecast- und Planungsrechnungen sowie Zulieferung von Daten zu Quartals- und Jahresabschlüssen
Anforderungen: Abgeschlossenes Studium der (Wirtschafts-)Mathematik oder ähnliche Qualifikationen; Kenntnisse auf den Gebieten der Versicherungs-/Finanzwirtschaft und Motivation zur aktuariellen Weiterbildung (DAV-Mitgliedschaft vorhanden oder angestrebt); Interesse an juristischen Fragestellungen aus Produktsicht; Schnelle Auffassungsgabe, sehr gute analytische Fähigkeiten, strukturiertes Arbeiten und Durchsetzungsvermögen; Spass und Motivation an Arbeit im agilen Umfeld in Verbindung mit Teamfähigkeit; Selbständigkeit, Initiative sowie Einsatzbereitschaft und Verantwortungsbewusstsein; Souveräner Umgang mit MS Office (Fokus Excel); Sehr gute Deutschkenntnisse mit Freude an der präzisen Anwendung der Sprache

Aufgaben: The successful candidate will have the opportunity to pursue a Ph.D. in Computer Science in the context of secure and privacy information extraction and processing, in the context of navigation of robots in indoor environments. The candidate will be required to perform the following tasks: Contribute to the project's success; Carry out research in the field of secure and privacy information extraction and processing; Disseminate results through scientific publications; Present results in well-known international conferences and workshops
Anforderungen: Master’s degree in Computer Science, Applied Mathematics, or, any related field; Programming skills, e.g., Python, C++, etc

Aufgaben: Research and build high-impact end-to-end machine learning systems for customer growth; Drive the design of scalable ML solutions in production; Coordinate the work of applied scientists and machine learning engineers providing research guidance and mentorship; Promote and role-model best practices of data science, engineering, and communication throughout the organization; Mentor engineers and data scientists across the org; Navigate existing ML and AI research and apply it to solve business problems
Anforderungen: M.S or B.S.in a Computer Science/Statistics/Data Science or related field; 10+ years of building products with Machine Learning and Personalization; Deep understanding of statistics and ML and AI fundamentals; Deep knowledge in multiple ML methodologies, such as LLMs, Foundation Models, Recommendations & Search, Causal Machine Learning, Interpretable ML, Multi-Armed Bandits, Reinforcement Learning and Constrained Optimization

Aufgaben: 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
Anforderungen: 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

Aufgaben: Analyse antibody sequences (liability screening, clustering, etc.) from Sanger and Next Generation sequencing platforms; Develop and implement computational pipelines and algorithms for analysing antibody sequences; Organize data storage in accessible formats for other team members; Prepare data summaries, overviews, and visualizations; Participation on in silico design of humanized antibodies; Integration of Electronic Lab Notebook system in the laboratory
Anforderungen: Master's or Ph.D. degree in Bioinformatics, Computational Biology, or a related field; Strong background in protein bioinformatics with a focus on sequence analysis; Knowledge of next-generation sequencing (NGS) data analysis and genomics databases; Proficiency in programming languages commonly used in bioinformatics such as Python or R; Familiarity with statistical methods and machine learning techniques applied to biological sequence data

Aufgaben: Research, design, and implement algorithms in Deep Learning for Medical Image Analysis problems; Close collaboration with clinical customers to define, implement and validate clinical prototypes; Advance the state-of-the-art, including generating patents and publications in top journals and conferences; Work on large-scale, real-world problems; Fast prototyping, feasibility studies, specification and implementation of image and video analysis product components; Working on challenging and impactful clinical problems with large-scale data sets
Anforderungen: Ph.D. in an engineering or science field such as Computer Science, Electrical Engineering, Statistics, or Applied Math; Strong background in Deep Learning and/or Medical Image processing; 4+ years of industry experience or post-doctoral studies in Computer Vision, Machine Learning and Image Understanding preferred

Aufgaben: Build machine learning solutions to respond to and mitigate business risks in ByteDance products/platforms. Such risks include and are not limited to abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc; Improve modeling infrastructures, labels, features and algorithms towards robustness, automation and generalization, reduce modeling and operational load on risk adversaries and new product/risk ramping-ups; Uplevel risk machine learning excellence on privacy/compliance, interpretability, risk perception and analysis
Anforderungen: Master or above degree in computer science, statistics, or other relevant, machine-learning-heavy majors; Solid engineering skills. Proficiency in at least two of: Linux, Hadoop, Hive, Spark, Storm; Strong machine learning background. Proficiency or publications in modern machine learning theories and applications such as deep neural nets, transfer/multi-task learning, reinforcement learning, time series or graph unsupervised learning

Aufgaben: Contribute to the design and analysis of algorithms for mathematical optimization and machine learning, and to the modeling for complex design, decision, and inference problems; Collaborate in the development and application of software instantiations of numerical algorithms; Document work and results in the form of journal papers and conference proceedings, and present work and results at scientific meetings and conferences; Bring creative and innovative perspectives by proposing algorithmic approaches, models, and solutions; Engage and interact with multidisciplinary science and engineering teams
Anforderungen: Ph.D. degree in applied mathematics, computer/computational science, data science, operations research, or a related field is required; Fundamental knowledge of mathematical optimization, statistics, or machine learning

Aufgaben: 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
Anforderungen: 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

Aufgaben: This role is available on the OCI AI Services and Data org. We are addressing exciting challenges at the intersection of artificial intelligence and cutting-edge cloud infrastructure. We are building state of the art data processing, model training and benchmarking platform. As Software Engineer on our team, we build services and tools to manage model lifecycle, model provenance, model catalog and model training. We build shared GPU super cluster that enables customers to easily onboard run, monitor and managing AI models at scale with OCI. You will have the opportunity to work on the LLM accelerators, setup ML training and benchmarking platforms, runtimes, libraries in the open-source projects that enable low friction performance optimized large scale training and inferencing of the world’s most advanced AI models
Anforderungen: Bachelor’s degree in computer science, engineering, or an equivalent highly technical field; 6+ years of software engineering experience and a proven track record of successfully architecting and shipping high performance, low latency AI/ML enabled products & services; Strong technical understanding in building complex, scalable, low latency streaming/batch processing AI/ML cloud services; Proven track record on running operations for a cloud service; Deep knowledge of large-scale compute, network, and storage systems; Experience working with Distributed Systems

Aufgaben: In this role, you will aid applied research and product development by conceptualizing, designing, and implementing engineering improvements related to large-scale deep neural networks. You would have proven expertise in efficiency optimizations using techniques such as quantization, model pruning, distillation, compute-efficient finetuning, etc. You have to be deeply knowledgeable in ML hardware and software to be successful in this role. Additionally, you need solid software development skills, a love of learning, a passion for solving problems, a bias to action, and effective collaboration with scientists
Anforderungen: 5+ years of software engineering experience with a track record of delivering quality results; Proven expertise in training and serving infrastructure for LLMs and other large foundation models; Strong problem-solving skills with knowledge of statistical methods; Strong software development experience in languages such as Python and Java; Deep understanding of TensorFlow and/or PyTorch

Aufgaben: Provide strategic direction for prenatal bioinformatics efforts, aligning strategies with company goals and collaborating with cross-functional teams; Lead the Bioinformatics team, fostering innovation, collaboration, and growth. Guide project priorities, resources, and career development; Develop and execute bioinformatics strategies to enhance next-generation sequencing pipelines for the Unity product line, driving innovation
Anforderungen: PhD in Bioinformatics, Computational Biology, Computer Science, Bioengineering, Physics or related field; Demonstrated ability to manage and lead a team of bioinformaticians; Excellent project management skills and attention to detail; Excellent communication and ability to work collaboratively with a cross-functional team; 10+ years of bioinformatics experience (including PhD years or afterward)

Aufgaben: Design and build core components of a first-of-its-kind data analytic application for maintenance and operations teams within asset intensive businesses; Grow your own skills and capabilities, surrounded by like-minded, crazy-smart, passionate creators focused on building best-in-class products for a huge, woefully underserved market; Create products from the ground up. From idea inception through design to detailed completion, all of your work will be on the critical path for the team and the business; Drive development of end-to-end data management solutions that span ad-hoc, batch and stream data processing at scale
Anforderungen: 5+ years of previous work experience and B.Sc. or M.Sc. in Computer Science or related field; Sound fundamentals and commitment to quality (read: not this guy https: //twitter.com/hipsterhacker ); Experience with Machine Learning, algorithm analysis, and data modeling; Experience with Scala and/or Java and JVM internals

Aufgaben: 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
Anforderungen: 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

Aufgaben: Conceiving of and conducting independent ML research, motivated by scientific milestones important to our team; Collaborating with colleagues across Flagship to apply our research to proprietary biological data and processes; Working with our ML Engineers to scale and interpret experiments
Anforderungen: PhD or MSc in a relevant field such as machine learning, computer science, math, physics etc. or equivalent practical experience; Significant deep learning experience relevant for position. Examples include geometric neural networks, generative modeling, representation learning, biological foundation models, multi-agent systems and reinforcement learning

Aufgaben: Accountable and responsible for Global Statistical Programming (GSP) study deliverables and submission activities for a group of Amgen products; Set and drive forward the programming strategies such as functional standards and industry requirements for the assigned product areas globally; Plan and monitor progress of projects and address issues accordingly; Support GSP Functional Service Provider (FSP) relationship and oversight; Ensure the product goals can be met via the FSP staff; Provide GSP product level input to developing and managing resource plans and budgets for GSP
Anforderungen: Doctorate degree and 2 years of statistical programming in Pharmaceutical industry experience; In depth knowledge of SAS Graph, SAS STAT, SAS Macro and SQL; Advanced SAS analysis and reporting skills; Prior regulatory submission experience; Thorough understanding and experience with data quality and compliance checks

Aufgaben: Design, implement and evaluate leading-edge machine learning methods related to cancer immunotherapy; Explore large-scale immunological datasets, including genomic, transcriptomic, mass spectrometry, and structural data, to derive and integrate orthogonal contributors of effective immunotherapy design; Stay abreast of scientific findings and technological developments and continuously improve computational methodology; Maintain detailed documentation of data analysis methods and results; Present findings and participate in cross-function team meetings
Anforderungen: PhD degree in Computational Biology, Bioinformatics, Computer Science, or a related field + 2 years of relevant experience, or MS degree + 5 years of relevant experience; Strong track record in machine learning algorithm development, preferably with applications in immunology, genomics, or personalized medicine; Proficiency in handling and interpreting large-scale biological datasets, including genomic and proteomic data; Strong programming skills in Python/R and with ML frameworks (e.g. PyTorch)

Aufgaben: Lead end-to-end data science Enterprise Excellence projects, from problem formulation to model deployment to address Citi Line of Business challenges and opportunities; Collaborate closely with cross-functional teams, including technology, re-engineering, product management, and business stakeholders, to define project requirements and deliverables; Apply advanced statistical and machine learning techniques to analyze large, complex datasets and extract actionable insights; Apply mathematical, problem-solving, and coding skills to manage big data, extracting valuable insights; Develop predictive models, algorithms, and data-driven solutions to optimize business process, improve product performance, and drive strategic decision-making; Design and conduct experiments, tests, and casual inference analysis to evaluate the effectiveness of interventions and initiatives
Anforderungen: Bachelor’s or advanced degree in Computer Science, Statistics, Mathematics, or related field; 6 to 8 years of relevant experience, with 4+ years of professional experience in data science, with strong foundation in statistical analysis, machine learning, and data visualization; Proficiency in programing languages such as Python, R, or Scala, and familiarity with libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, or spark; Solid understanding of experimental design, hypothesis testing, and casual inference methods; Experience with SQL and relational databases for data manipulation and querying; Proficiency with data mining, mathematics, and statistical analysis

Aufgaben: 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
Anforderungen: 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

Aufgaben: Research and develop our machine learning systems, including heterogeneous computing architecture, management, scheduling, and monitoring; Manage cross-layer optimisation of system and AI algorithms and hardware for machine learning (GPU, ASIC); Implement both general purpose training framework features and model specific optimisations (e.g. LLM, diffusions); Improve efficiency and stability for extremely large scale distributed training jobs; Plan and lead the development of new and advanced data analytic techniques, methodologies and analytical solutions from design, prototyping, and testing; Identify and develop core data and AI science components for the delivery of projects, architect specialised database and computing environments, explore and visualise complex data set to provide incremental business value
Anforderungen: Bachelor or above degree in distributed, parallel computing principles and know the recent advances in computing, storage, networking, and hardware technologies; Familiar with machine learning algorithms, platforms and frameworks such as PyTorch and Jax; Have basic understanding of how GPU and/or ASIC works; Expert in at least one or two programming languages in Linux environment: C/C++, CUDA, Python