Aufgaben: Lead, collaborate, and execute on research that pushes forward the state of the art in multimodal reasoning and generation research; Work collaboratively with other research scientists to develop novel solutions and models in service of contextualized AI for augmented reality; Working on curation of large datasets across many modalities (e.g., vision, audio, IMU, sEMG); Leading experimental design, implementation, evaluation, and reporting results to enable new capabilities for multimodal LLMs
Anforderungen: PhD degree or equivalent experience in Computer Science, Mathematics, Engineering or a related field; Publication record in machine learning, AI, computer science, statistics, applied mathematics, data science, or related technical fields; 6+ years of experience in one or more of the following areas: Deep Learning, NLP, Multimodal, Computer Vision, Speech

Aufgaben: Designing, developing, building, and maintaining peptide design pipelines, focusing on (but not restricted to) structural and conformational aspects; Maintaining a scientific and technical watch and staying abreast of the state-of-the-art in the fields of protein structure prediction and peptide and protein design, from both global research and industrial perspectives; Performing structural analyses of systems of interest (detection of pockets, detailed analysis of protein/protein interfaces, of docking pose, etc.); Engaging with other peptide and protein design companies to develop partnerships or to conduct joint projects
Anforderungen: Ph.D. in computational chemistry, molecular modeling, structural biology, machine learning, or a related field, with a strong theoretical background as demonstrated by contributions to leading journals; or an equivalent combination of education and experience; Hands-on experience designing, training, or utilizing modern deep-learning tools for protein structure prediction, protein modeling or protein design (e.g. AlphaFold, ProteinMPNN, Rosetta tools etc.); 3 or more years of experience in protein structure prediction and analysis, including expert knowledge of modern computational chemistry packages and tools, with an emphasis on molecular dynamics, structure prediction and analysis, virtual screening/docking

Aufgaben: You will be involved in specific engagements involving the building of new and bespoke advanced analytics solutions for clients. You’ll dive into complex data sets across a rich variety of industries, functions and geographies while remaining a core member of the strategy team, injecting your analytics thinking on meaningful client projects. You will shape solutions tailored to the needs of our clients, maximizing programming languages (e.g., R, Python), tech platforms, and disruptive analytics methodologies (e.g., Casual Inference, Bayesian Optimization, Geospatial Analytics, Natural Language Processing) as part of our tech-agnostic firm
Anforderungen: Bachelor’s degree in quantitative field like computer science, engineering, statistics, mathematics or related field required; advanced degree is a plus; Programming (focus on machine learning) in Python (must), SPSS, SAS, Ruby, Hadoop (valued); 3+ years of hands-on mathematical modelling experience in business environment

Aufgaben: Responsible for business data collection and consolidation; Build robust data analytics models and identifying potential loss trends; Responsible for scripting excel macro (VBA) and R algorithms; Providing comprehensive analysis of data and output of user-related data analysis; Being the main local point of contact for any analytics topics; Dashboarding and production of presentation of analytics’ results; Validating a variety of client financial and non-financial data for the use in risk advisory services
Anforderungen: A Bachelor’s degree or professional qualification in Statistics, Actuarial Science or Data Science preferred; Preferable working experience as a data analysis and statistical modelling; Good command of spoken and written English, Cantonese & Mandarin; Proficient in MS Office, namely Word, Excel (i.e. Macros and VBA) and Power Point; A good understanding and working knowledge of statistical modelling

Aufgaben: Leverages AI and ML techniques to develop and deploy innovative solutions that improve business outcomes in the healthcare industry, ensuring patient privacy and data security requirements are met; Collaborates with cross-functional teams, including data scientists and software engineers, to integrate AI solutions into existing products and services across various prioritized use cases within the enterprise AI roadmap; Develops and implements machine learning models and algorithms to solve complex business problems and enhance AI-driven applications; Models, builds, and tests AI software to ensure it can handle large volumes of data and deliver desired outcomes; Converts AI/ML models into APIs that can be utilized by other developers to enhance application functionality
Anforderungen: Bachelor's degree Bachelors in Computer Science, Data Science, Bioinformatics or related field. required; 5-7 years Experience as an AI Engineer or in a similar role. required; Sound understanding of patient privacy and data security requirements, with direct experience applying AI in healthcare being a plus; Superior written and presentation skills to effectively communicate complex AI concepts and solutions; Proficiency in programming languages such as Python, R, and other common AI languages

Aufgaben: Evaluating large and complex data sets for the purpose of correlative and causal pattern discovery, trend driver analysis, predictive modeling, and financial forecasting; Developing programming solutions to address unique situational needs, calling upon a diverse array of analytics methods and programming languages; Build dashboards and exhibits that monitor key metrics and derive insights for a wide range of audiences; Collaborate closely with and provide analytical guidance to Lockton consulting teams: strategic, clinical, pharmacy, account service, etc; Responsible for accurate and thorough documentation of product/components; Requirement clarification, design, and implementation for software product/solution releases
Anforderungen: 2+ years of relevant data analytics programming and/or insurance company experience, and an understanding of risk and insurance; Experience developing Machine Learning models and Predictive Analytics algorithms; Bachelor’s or master’s in data science, computer science, operations research, statistics, actuarial mathematics, applied mathematics, or a related quantitative field; Ability to manage/maintain large data sets and process through various software, applications, and programming languages: Excel, PowerBI, PowerQuery, SQL, R, Python, SAS, etc

Aufgaben: As an Expert Data Scientist at QuantumBlack you will work in multi-disciplinary environments harnessing data to provide real-world impact for organizations globally. In this role, you will influence many of the recommendations our clients need to positively change their businesses and enhance performance. You will work on complex and extremely varied data sets from some of the world’s largest organizations to solve real world problems. You will develop data science products and solutions by writing highly optimized code to advance our internal Data Science Toolbox for clients, as well as for our data science team
Anforderungen: Master's degree or PhD level in a relevant field such as computer science, machine learning, applied statistics, mathematics; 10+ years of deep technical experience in distributed computing, machine learning and statistics related work; Programming experience in languages such as Python, R, Scala, SQL

Aufgaben: In this role, your work on the team will primarily be in applying advanced analytics to enable better commodity risk management decisions. For example, you might work as the lead in maintaining and expanding existing hedging strategies by re-training existing models through process driven approaches. You might also modify and improve algorithm performance across market regimes, by introducing new features, data sources, and modelling approaches; rapidly identify opportunities for our clients to increase earnings potential and reduce downside risk by back testing various risk management strategies; co-build bespoke tools with client data science teams that tailor machine-learning algorithms to attain an optimal balance of earnings and volatility given clients’ risk appetite and capital constraints; and/or collaborate with and train cross-functional client teams to instill long-lasting capabilities and ensure new decision-making models are embraced by organizations
Anforderungen: Undergraduate degree is required; advanced degree in a quantitative discipline such as computer science (especially machine learning), applied mathematics, economics, quantitative finance or engineering is preferred or equivalent practitioner experience; 2+ years of commodity markets experience developing trading or hedging strategies (especially physical/cash markets) or price-discovery analysis in basic materials/metals, agriculture, softs, chemicals, plastics or oil & gas preferred; Experience writing clean, efficient Python code involving model development and deployment using state-of-the-art tools and libraries (e.g. scikit-learn, pandas, etc.)

Aufgaben: Will be part of a highly effective team of Biomarker Clinical Programmers. Work collaboratively with Biomarker Clinical Data Associates, Biomarker Statistical Programmers, Bioinformatics, Biomarker Scientists and Biomarker/BioAnalytical Operations to meet project deliverables. Work with internal colleagues, offshore resources, and external vendors to ensure efficient, high-quality production of curated data for downstream use in sample tracking, production of statistical outputs for clinical study reports, biomarker analysis reports in support of Gilead’s regulatory, scientific, and business objectives
Anforderungen: 6 years of experience and a BS degree in Biostatistics/Computer Science or equivalent, or 4 years of experience and a MS degree in Biostatistics/Computer Science or equivalent; Experience in SAS programming required; Experience with Python strongly preferred

Aufgaben: This is an exciting opportunity to join our company’s AI CoE team which is transforming healthcare and improving the lives and vitality of the millions of members we serve. We leverage cutting edge Artificial Intelligence (AI) and Machine Learning (ML) algorithms to develop solutions for automated document processing and customer service chat bots. Your focus will be developing the best fit solutions leveraging Large Language Models (LLMs) and Generative AI solutions including but not limited to BERT, RoBERTA, and GPT for a number of Natural Language Processing (NLP) tasks
Anforderungen: Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related fields; 7+ years of experience in core AI techniques including NLP (Natural Language Processing), ML (Machine Learning) and Deep Learning; 1+ years of direct Generative AI (GenAI) and building LLMs experience; Research experience with sequential modeling or generative AI, deep learning architectures, and Transformers, with a strong understanding of deep learning techniques such as GPT, VAE, and GANs; Programming experience in C/C++, Java, Python, computer vision, self-supervised learning, transfer learning, and reinforcement learning

Aufgaben: Data Processing: Uses existing tools to build data processing pipelines to convert raw data into formats compatible with conventional statistical analysis and visualization. Adapts tools when necessary; Data Analysis: Performs routine analysis for which established tools exist and are considered reliable; Keeps up with the computational biology literature to assure pipelines components are up to date. Adapts tools when necessary; Data and Software Management: Monitors, downloads, organizes, and manages data from public data repositories or generated by collaborates. Evaluates published tools and updates pipeline as necessary. Writes scripts that perform this automatically
Anforderungen: Bachelor's degree required in a STEM field. Master’s degree preferred in bioinformatics, computational biology, statistics, biostatistics, computer science and/or the life sciences; 2 years with Bachelor’s degree or 1 year with Master’s degree; academic research experience or authorship in scientific publications experience may substitute for work experience

Aufgaben: Develop computational methodology and perform critical analyses to support development of new products and improvements to existing products, both as an individual contributor and/or as a team leader; Collaborate with cross-functional teams including members from assay development, software engineering, marketing, quality, regulatory, and others to execute complex product development projects; Work closely with bench scientists to develop and optimize new wet-lab protocols in concert with computational biology development efforts; Analyze large genomic and epigenomic datasets using cutting-edge computational biology methods to identify genomic alterations and biomarkers associated with cancer onset and progression and to craft novel tools to detect those patterns
Anforderungen: PhD in a life science or computational discipline; 5+ years of postdoctoral research or professional experience related to NGS or cancer diagnostics

Aufgaben: Programming edit checks for Data Management with SAS; Create tables, listings and figures for clinical study report; Annotated blank CRF (acrf.pdf) following FDA/CDISC or sponsor guidelines; Create or QC SDTM specifications and SDTM datasets; Create or QC ADaM specifications and ADaM datasets; Create Study Data Reviewer’s Guide (cSDRG.pdf) and Analysis Data Reviewer’s Guide (ADRG.pdf); Create define.xml or define.pdf following FDA/CDISC or sponsor guidelines
Anforderungen: Bachelor’s degree in computer science (CS), statistics or related scientific disciplines with 7 yrs. clinical programming experience; Master’s degree in CS, statistics or related disciplines with 6 yrs. of clinical programming experience; Working knowledge of ICH and Good Clinical Practices, Clinical research, Clinical trial process and related regulatory requirements and terminology; Good understanding of clinical drug development process

Aufgaben: Conduct offline and online experiments, analyze according data and evaluate to improve algorithms and strategies; Responsible for the research and development of cutting-edge machine learning technology, application of visual, speech, audio and text recognition post-processing technology to products; Responsible for the optimization of NLP/Computer Vision/MultiModal algorithms for content understanding, and applying them to the scenarios of Trust and Safety; Responsible for building the ML model to recognize inappropriate content in the Trust and Safety context
Anforderungen: Bachelor's degree in Computer Science or equivalent with 5+ years of experience; Familiar with large-scale language modeling algorithms (N-gram, nnlm); Familiar with decoding engine optimization, with experience in WFST composition and optimization; Familiar with decoding algorithms under the end-to-end framework, with experience in decoding algorithm development and optimization

Aufgaben: Individually contribute to data science and machine learning R&D projects; Use your data science, machine learning, and/or computer science skills to conduct research and contribute to solutions to technology and business problems; Contribute to projects from early-stage research through development; Implement and optimize state-of-the-art algorithms in distributed environments; Develop an understanding of Epsilon PeopleCloud Digital Media Solutions personalization platform and proprietary datasets; Participate fully in our collaborative approach to research and applications projects
Anforderungen: Ph.D. in a computational, mathematical, engineering, or scientific field; Fluency in computer programming, data structures, and algorithm design; Proven analytic and modeling skills; Proven ability to conduct research projects

Aufgaben: Contribute up and down the stack from data exploration, creating data pipeline, generating insights/features, building ML models to deploying them; Support on R&D/discovery pilot projects where we enable clients to understand their data and problems which can be solved using the platform; Work closely with a team of ML Engineers, Data Engineers, and Product Managers to build and deploy machine learning models; Play an active role in leading team meetings and workshops with clients; Rotate between client project work and internal product development in alignment with your personal development plan
Anforderungen: Master of Science or PhD - Data Science or any related field; Have previously built insights from ML models, building explainable ML models and not just black box algorithms; Demonstrates the ability to make "Data Driven Decisions" and has the ability to communicate why those decisions make sense; Excellent communication with technical and non-technical teammates as well as clients. Prior experience in a client facing role will be necessary; Understands the importance of "Data exploration" (in Jupyter notebooks/SQL) as well as building models and setting up data/ML pipelines

Aufgaben: 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
Anforderungen: 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

Aufgaben: Contribute to the development of data science methodologies, frameworks and best practices across customer/stakeholder archetypes; Develop and implement advanced analytics models and mentor others on the use and application of those modeling techniques; Support brand-related strategies, opportunity discovery and investment decisions with advanced analytics (examples include Customer Segmentation, Patient Adherence Analysis, HCP Network Analysis, etc.); inform global, regional and local brand related decisions; Implement marketing performance measurement processes such as Marketing Mix Optimization, brand tactics/campaign assessment ROI, etc
Anforderungen: Bachelor’s degree in business-related field; Minimum 6 years of pharmaceutical analytics, operations or related experience required that includes data analysis and reporting, or seven years with Master's degree and related experience required, with demonstrated success in managing related teams and projects of increasing size and complexity; Recent hands-on experience with statistical modeling techniques and their application within complex analytical projects (e.g., regression/promotion response modeling, ROI, correlation coefficient, etc.)

Aufgaben: Research and implement efficient AI/machine learning (ML) algorithms and feature exploration methods Develop worfklows from existing algorithms, or modify bioinformatics methods to analyze next generation sequencing (NGS) data, including but not limited to long-read sequencing, RNA-seq, whole genome sequencing (WGS), scRNA-seq. Develop and implement novel algorithm and methods for NGS data types to meet R&D objectives, and the demonstration of the validity of the methods through prototypes and benchmarking using appropriate controls
Anforderungen: PhD in Computer Science, Bioinformatics, Molecular and Cell Biology or related disciplines; 4+ years of hands-on experience with gene expression/NGS data analysis using AI/ML; Expertise with common NGS visualization and processing tools (e.g., IGV, samtools, DESeq2); Proficiency in Linux/Bash, Python and R; Familiarity with Cloud

Aufgaben: Scale and build infrastructure for predictive models on large-scale datasets to address various business problems; Transform requirements into architectural and feature specs; Mentor and provide technical guidance to junior engineers, review code, and ensure alignment with best practices in software development and AI/ML engineering; Collaborate with product management and engineering groups to develop new products and features; Work closely with teams across Adobe, in different geographies. The technology you produce will have visibility at the highest levels of the company
Anforderungen: 7+ years of industry work experience. Good sense of product with a focus on shipping user-facing data-driven features; Proficient in one or more programming languages, such as Python, Java, or Scala; Familiar with one or more machine learning, deep learning, or statistical modelling tools such as R, scikit-learn, and JupyterLab; Familiar with public cloud computing platforms and frameworks such as DataBricks, SageMaker, and Tensorflow

Aufgaben: The Data Scientist, Ophthalmology Brand Analytics plays a critical role in providing valuable strategic business insight and actionable recommendations to global and priority Commercial Division/markets to support achievement of brand objectives for priority/strategic products. This position is responsible for assessing performance on an ongoing and ad hoc basis to identify new business opportunities and insights and advise key stakeholders on how best to leverage the opportunities. In addition to providing sound counseling and objective interpretation of data to the stakeholders in global and regional commercial functions
Anforderungen: Bachelor’s degree in business-related field; Minimum 6 years of pharmaceutical analytics, operations or related experience required that includes data analysis and reporting, or six years with Masters degree and related experience required, with demonstrated success in managing projects of increasing size and complexity; Proficiency in coding language (e.g. SQL, SAS, R, or Python)

Aufgaben: We are looking to hire a Senior Machine Learning Engineer with a proven record applying cutting-edge techniques to create seemingly magical software features for Health products. We want you to be technically deep, and a strong communicator who can work effectively with our partner engineering teams. You will help Apple push the boundaries of artificial intelligence to make life-improving Health and Wellness-driven product experiences for billions of customers around the world!
Anforderungen: MS or PhD in Computer Science or similar field, or equivalent experience; Experience or strong personal curiosity about building consumer digital health and wellness products; Hands-on experience productizing machine learning driven experiences from conception to shipped product; Deep knowledge of Objective-C, Swift, or C/C++, with significant experience developing production code for a shipping product

Aufgaben: Strategische Geschäftsmodelle zur Innovation und Effizienzsteigerung gemeinsam mit wesentlichen Entscheidern beim Kunden erarbeiten; Je nach gewünschtem Fokus: fachliche oder technische Herausforderungen analysieren und Lösungsansätze entwickeln; Im Programm-Management erste Steuerungsaufgaben für Transformationen und in IT-Umsetzungsprojekten übernehmen
Anforderungen: Sehr guter Hochschulabschluss in Physik, Mathematik oder einem anderen naturwissenschaftlichen Studiengang; Interesse an strategischen Fragestellungen grosser Konzerne, u.a. im Digitalisierungskontext; Überdurchschnittliches Abstraktionsvermögen, Teamgeist und analytische Denkweise

Aufgaben: KIT; The Research University in the Helmholtz Association; combines university tradition with program-oriented research. In 2009, the Technical University of Karlsruhe and Karlsruhe Research Center merged to KIT. The framework conditions presently offered to KIT researchers are accordingly unique in the German science system. Nowhere else can researchers use the infrastructure of a large-scale research center and collaborate at a university of excellence across the disciplines of natural sciences, engineering, economics, the humanities and social sciences. Research at KIT is aimed at creating new findings, applications, and solutions to master the global challenges facing humankind with pathbreaking contributions; in particular in the areas of energy, mobility, and information. The only German university of excellence with a national large-scale research sector offers unique education and training options for students and early-stage researchers
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Aufgaben: Lifeware was founded in 1998 in Switzerland, when a leading group of mathematicians, physicists and computer scientists decided to combine their expertise and innovative thinking about the life insurance business into their own company. A complete, fully integrated, web based solution for the management of life insurance products: this is Lifeware service
Anforderungen: We crawl all higher jobs at Lifeware automatically and post them at acad.jobs. Additional jobs can be found by clicking here. Many more institutions are listed in the left frame (online version), see "Search yourself at 8000 institutions"