Duties: Conduct end-to-end computational analyses of single cell and spatial transcriptomics data; Contribute to establishment and maintenance of single-cell and additional bioinformatics processing pipelines; Implement tools for cross-dataset and multi-omics data harmonization, integration, and visualization; Develop and implement innovative computational biology algorithms and data science approaches towards identification and in-silico validation of novel immuno-oncology targets and biomarkers; Advance analytics support for in-vitro and in-vivo validation of drug targets, mechanism-of-action (MOA) analysis, patients’ stratification and biomarkers discovery
Requirements: Ph.D. or equivalent hands-on years of experience in Bioinformatics/Computational Biology & Data Sciences; Strong programming and data science skills (Python or R preferred); Hands-on experience in data analysis workflows of RNA-Seq and single-cell RNA-Seq; Ability to propose and carry out independently computational biology research projects; Demonstrated impact via the development of novel innovative algorithms/analyses and the adoption of available open source or licensed solutions

Duties: Lead and individually contribute to data science and machine learning R&D projects; Use your expertise in data science, machine learning, and computer science to lead research projects and recommend solutions to technology and business problems; Interview candidates for open positions on our team; Lead and contribute to projects from early-stage research through development, in consultation with stakeholders; Provide technology leadership to yield innovative differentiating solutions; Implement and optimize state-of-the-art algorithms in distributed environments
Requirements: Ph.D. in a computational, mathematical, engineering, or scientific field; Fluency in computer programming, data structures, and algorithm design; Proven analytic and modeling skills; proficient at implementing, and evaluating accurate and scalable solutions to business problems; Proven ability to lead development projects from conception through deployment; Proven ability to lead and conduct research projects; 2+ years of industry experience in a computational area such as data science, computer science, machine learning, artificial intelligence, statistics, or graph algorithms

Duties: The Bioinformatics Engineer plays an important role in the quality control, assembly, annotation, and dissemination of microbial (bacterial and viral) genomes in a military medical research setting. While the primary task for the Bioinformatics Engineer is to assist in microbial genome assemblies and downstream analyses to a complete (polished genome) standard, they will also contribute to other tasks such as analysis of RNAseq data and bioinformatic pipeline development and testing
Requirements: Candidates must have completed a Bachelor’s or Master’s degree from an accredited US university, or international university of equivalent standard, in Bioinformatics, Computer Science (combined with experience or education in biology or bioinformatics), Computational Biology, Mathematics or a closely related area; Candidates must have at least 2-4 years of hands-on experience in Bioinformatics; Possess programming skills in languages such as JAVA, PERL, PYTHON, and statistical software such as R or R Studio; Maintain a familiarity with next generation sequencing and microarrays

Duties: Develop and implement machine learning algorithms to solve business problems; Design and implement scalable data processing and machine learning pipelines; Collaborate with product, engineering, and data teams to identify machine learning opportunities; Evaluate and improve the performance of machine learning models; Stay up-to-date with the latest developments in machine learning research and apply them to real-world problems; Write clean, scalable, and maintainable code; Communicate technical concepts and ideas to both technical and non-technical stakeholders
Requirements: PhD or Masters's Degree in Computer Science, Mathematics, or Statistics a similar technical field of study with a specialisation in Machine Learning, Data mining, Information Retrieval or Data science; 10+ years of industry experience in building production-grade machine learning systems with all aspects of research, model training, tuning, deploying, serving and monitoring. Industry experience in ecommerce, recommender systems, digital marketing or two-sided marketplaces is a plus

Duties: Improve existing pipelines for content acquisition; Develop, train, and validate machine learning models to target various use cases for biological literature; Use a variety of NLP libraries and techniques for entity recognition and relationship extraction; Contribute to quality control and reliability efforts for our processes, pipelines, tools, and models that support development, build, and maintenance our biological content
Requirements: Graduate degree in bioinformatics, computer science, or related field combined with 5-8 years of experience in NLP engineering; Proficiency inJava or Python and a demonstrable ability to quickly learn; Solid understanding of the deep learning ecosystem; Experience with machine learning algorithms and frameworks such as PyTorch or Tensorflow; Experience with word embeddings and language models such as Word2Vec or BERT

Duties: Leading and managing team of internal and external biostatistics and statistical programming resources supporting studies and programs for identified therapeutic area(s) or phase(s) of development.Managing assignments and priorities of team members; Ensuring accurate, statistically valid deliverables included in protocols, statistical analysis plans, study reports, manuscripts, and regulatory submission documents; Coordinating achievement of major statistical deliverables and milestones in collaboration with other functions; Leveraging standardization to maximize global data integration and interpretability; Providing statistical leadership and support for feasibility assessments, clinical development plans, complex study designs, regulatory meetings, submissions and follow up; Providing statistical leadership for preparation of marketing applications (NDA/BLA) to FDA, EMA, or other worldwide regulatory agencies
Requirements: A PhD in Statistics/Biostatistics and at least 7 years of relevant pharmaceutical experience or a MSc in Statistics/Biostatistics and at least 10 years of relevant pharmaceutical experience; Comprehensive knowledge of statistical methodology in design and analysis of clinical trials including Bayesian modeling and adaptive design; regulatory requirements relating to clinical development of drugs and biologics; BLA/NDA experience including eCTD submissions; Working knowledge of major statistical software programs including SAS; Knowledge of CDISC requirements for SDTM and ADaM

Duties: für Studierende und Absolventen, Erfahrene; alle Disziplinen
Requirements: kann auch für Stellengesuche verwendet werden

Duties: The Swiss National Science Foundation (SNSF) funds excellent research at universities and other institutions; from chemistry to medicine to sociology. Thousands of teams are generating knowledge for a better future for all. Together with our partners, we play a key role in shaping research in Switzerland
Requirements: We crawl all higher jobs in research, teaching and administration at SNF 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"

Duties: Work as a statistician on clinical trials; producing and validating complex outputs to excellent quality whilst adhering to deliverable timelines. Producing and reviewing Statistical Analysis Plans (SAPs), protocols and other pertinent study documentation. Acting as lead statistician within a reporting team environment, being responsible for statistical aspects of reporting out study results. Working as a global lead statistician across multiple studies, overseeing more junior leads and supporting regulatory interactions. Preparing randomisation schedules and acting as the unblinded statistician on reporting teams. Acting as a statistical consultant to pharmaceutical or biotech companies. Excellent team work ethos, and willingness to help others. Potential to have line management responsibilities
Requirements: PhD or MSc in Biostatistics or related discipline; Experience within the pharmaceutical industry to have a good awareness of clinical trial issues, design, and implementation. Familiarity with GCP and regulatory requirements

Duties: 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
Requirements: 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; Research experience in a computational area such as data science, computer science, machine learning, artificial intelligence, statistics, or graph algorithms

Duties: Design, prototype, implement, evaluate, optimize and monitor machine learning algorithms and related software systems to generate sports data and insights with high accuracy and low latency; Build, test, deploy and maintain production systems; Maintain and promote best practices for software development, including deployment process, documentation, and coding standards; Contribute to technical and product discussions, and share knowledge and ideas with colleagues across the company
Requirements: BSc or MSc or equivalent experience with a strong software engineering component; Experience with deep learning and some of the languages and technologies in our stack; Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback

Duties: Conduct end-to-end computational analyses of single cell and spatial transcriptomics data; Contribute to establishment and maintenance of single-cell and additional bioinformatics processing pipelines; Implement tools for cross-dataset and multi-omics data harmonization, integration, and visualization; Develop and implement innovative computational biology algorithms and data science approaches towards identification and in-silico validation of novel immuno-oncology targets and biomarkers; Advance analytics support for in-vitro and in-vivo validation of drug targets, mechanism-of-action (MOA) analysis, patients’ stratification and biomarkers discovery
Requirements: Ph.D. or equivalent hands-on years of experience in Bioinformatics/Computational Biology & Data Sciences; Strong programming and data science skills (Python or R preferred); Hands-on experience in data analysis workflows of RNA-Seq and single-cell RNA-Seq; Ability to propose and carry out independently computational biology research projects; Demonstrated impact via the development of novel innovative algorithms/analyses and the adoption of available open source or licensed solutions

Duties: Develop long term strategy for scaling the routing and delivery optimization systems; Lead the team in model and algorithm development by taking business requirements and complex problem statements, and clearly defining data science/statistical projects; Develop and operationalize machine learning and science-based tools/models iteratively to support growing business use cases and complexity; Develop and deliver on key performance indicators for financial impact, customer impact, labor impact, and more
Requirements: 8+ years in routing, optimization, machine learning, data science, and/or engineering positions in top CPG, retail, or e-commerce organizations; 5+ years’ experience managing people and leading a team of leaders; An advanced degree (M.S., Ph.D., or equivalent experience) in Statistics, Applied Mathematics, Engineering, Computer Science, or related field; Proven experience with bringing structured thinking in ambiguous problems spaces and delivering solutions; Experience with machine learning and advanced optimization methodologies

Duties: The position entails teaching at undergraduate and graduate levels, and strong engagement with practice and the business community. Key Duties and Responsibilities: The appointed candidate will be expected to: 1. Develop and teach undergraduate and postgraduate courses in statistics; 2. Engage in innovative and technology-based approaches to learning and teaching; 3. Publish high quality research in leading internationally recognized journals; 4. Participate in the supervision of undergraduate and postgraduate research projects and/or dissertations
Requirements: A PhD in the field of statistical science from an internationally recognized university

Duties: Teaching statistics and mathematics across the baccalaureate spectrum; Conducting scholarly activity that advances the professional and scholarly goals of the faculty member, the Department of Mathematics, the College of Science, and the University; Advising and mentoring students as they progress through their academic careers; Participating in service activities at the Department, College, and University levels
Requirements: A doctorate in Statistics, Statistics Education, or closely related field, earned by August 14, 2024, is required. For those with a doctorate in Statistics Education, a master's degree in Statistics, Mathematics, or closely related field is required

Duties: Develop and teach undergraduate and postgraduate courses in statistics; Engage in innovative and technology-based approaches to learning and teaching; Publish high quality research in leading internationally recognized journals
Requirements: A PhD in the field of statistical science from an internationally recognized university

Duties: Conceive, develop, and deploy robotic and automation software solutions for advanced manufacturing applications and perception-driven solutions; Design, build, debug and implement robotic and automation solutions. Spec, develop pipelines, and implement on hardware perception and perception enabled solutions for high mix environments; Develop and test advanced software solutions for manufacturing and industrial processes and technologies; Assist in preparing proposals and cost estimates. Meet with customers to promote new business and develop technical requirements
Requirements: Requires a Bachelors, Masters, or a PhD in Robotics, Mechanical Engineering, Electrical Engineering, Software Engineering, or Computer Science or similar (PhD requires 0 years, MS requires 1, and BS requires 2); 2 years experience: Development of electromechanical and robotic systems from concept to deployment (full spectrum of robotic solution development); Development work using C, C++ or python

Duties: Perform engineering design and analysis of complex fluid flow systems in support of validation testing or other research studies for external and internal customers; Use of Creo and/or SolidWorks preferred; Conduct evaluations and reviews of system designs with a mind for safe operation of high temperature/pressure systems; Communicate with clients to arrange for conducting experiments and testing including quoting/bidding the cost to test based on their requirements; Coordinate with the team of engineers and technicians to execute all preparation, safety assessment, setup, testing, and data processing tasks needed for each project; Ensure strict adherence to test procedures and safety protocols to maintain compliance with the Quality Management System, and work with the team to document and close any non-conformances
Requirements: Requires a Bachelors in Mechanical Engineering or directly related engineering degree; summer internship or undergraduate research in the area of: petroleum systems, complex fluid flow systems, fluid rheology or similar field

Duties: Computer simulations of materials under shock and impact; Testing of materials with MTS, Hopkinson Bar, Plate Impact, ballistic impact, etc; Develop algorithms in MatLab, Python, FORTRAN, or similar for high strain-rate applications; Use of lasers in various applications; Use of digital image correlation
Requirements: Requires a PhD in Mechanical Engineering, Materials Engineering) or Nuclear Engineering; Previous experience with computer codes applied to impact problems is a plus

Duties: Develop models for fluid thermal systems using 1D finite volume of finite element principles. This may include the use of off the shelf software such as Hysys, NPSS, or fluent; Develop and validate simulations for control strategies for fluid thermal systems using 1D finite volume of finite element principles. This may include the use of off the shelf software such as Hysys, NPSS, or fluent; Develop improved or optimized piping system designs/improvements for existing or planned systems based off of model feedback; Run cycle analysis and optimize cycles for refrigeration and power generation
Requirements: Requires a Bachelors, Masters or a PhD in Mechanical Engineering. experience in Thermal fluid system modeling and control background. Graduate experience in developing model and control algorithms for thermal fluid piping systems is preferred

Duties: Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed; Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations; Build and prototype analysis pipelines iteratively to provide insights at scale; Develop comprehensive knowledge of data structures and metrics, advocating for changes where needed for product development
Requirements: 3+ years industry experience and advanced degree in quantitative discipline (e.g., Statistics, Operations Research, Economics, Computer Science, Mathematics, Physics) or equivalent practical experience; Deep knowledge of experiment design and causal inference, strong analytical and causual reasoning mindset; Fluency in core set of Data Science, and SQL/Hive, R/Python, and ETL

Duties: Conduct fluid system modeling for applications in launch vehicles and turbomachinery using engineering software; Be a solution-oriented problem solver that exercises creativity and independent judgement in determining approaches to solve a wide range of technical problems with moderate supervision; Write technical reports, papers, proposals and prepare technical presentations for client meetings and conferences; Design, analysis, and test support for fluid/thermal projects within the Department, such as combustion, turbomachinery primary and secondary flows, aerodynamic design, supercritical CO2 power systems, heat exchangers, gas system design and modeling
Requirements: Requires a Bachelors in Mechanical Engineering, Aerospace Engineering, or related engineering degree; 0-5 years expierence in conducting fluid and thermal systems analyses using commercial software, such as flow network solvers or computational fluid dynamics (CFD) solvers

Workload: 30-50%
Duties: Sie vermitteln im Mathematikunterricht den angehenden Ingenieurinnen und Ingenieuren das für ihre Fachausbildung und die spätere Berufstätigkeit grundlegende mathematische Wissen; Sofern Sie ausserdem über fundiertes Wissen in Physik verfügen, besteht die Möglichkeit, zusätzlich im Physikunterricht eingesetzt zu werden; Sie setzen sich mit Begeisterung für Ihr Fach und für qualitativ hochstehende Lehrveranstaltungen ein
Requirements: Hochschulabschluss in Mathematik oder eine äquivalente Ausbildung (Promotion und fundierte Kenntnisse in Physik sind von Vorteil); Interesse an Ingenieuranwendungen der Mathematik im Unterricht; Engagement bei der Weiterentwicklung der Lehre; Lehrerfahrung ist erwünscht (Unterrichtssprache ist Deutsch)

Duties: Absolviere unser Digital Transformation Traineeprogramm im Ausmass einer Vollzeitbeschäftigung in einem der folgenden Bereiche: Risk, Finance or Accounting; Kundenbetreuung (im Retail, Corporate Banking und Private Banking); Informatik & Kommunikation (Omnikanal Management); Innovation und Projektmanagement
Requirements: Abgeschlossenes Bachelor- bzw. Masterstudium Uni/FH oder; Abgeschlossene höhere Schule mit Matura; Sehr gute IT-, sowie Deutsch- und Englischkenntnisse; Grosses Interesse, sich gestalterisch und innovativ einzubringen; Hohes Mass an Engagement, Flexibilität und Teamfähigkeit

Duties: Mitwirkung bei der Aufbereitung der Modellentwicklungsdaten mittels gängiger Datenanalysetools (z.B. SQL, Python, R, SAS) und Modelle hinsichtlich Repräsentativität der Daten, Qualitätskriterien Check und Verbesserung der Qualität; Mitarbeit an den IRB relevanten Konzepten und Modelldokumentationen, die im Aufgabenbereich des Teams liegen; Übernahme Modell Ownership für eines oder mehrere Kreditrisikomodelle; Laufende Schnittstelle zur Aufsicht zu Kreditrisikothemen, der internen Revision und des Vorstandes; Mitarbeit bei der Weiterentwicklung von risikorelevanten Attributen und deren Aufschliessung im Data-Warehouse
Requirements: Abgeschlossenes Studium (Wirtschaftswissenschaften, -informatik, Betriebswirtschaft, Volkswirtschaft, Statistik, Mathematik); Erfahrung im Risk Management im Bankenumfeld von Vorteil; Mathematisches/statistisches, technisches Verständnis und IT-Affinität; Grundlegende Programmierkenntnisse (insbesondere SQL, Python und SAS) und gute Kenntnisse hinsichtlich Datenstrukturen, Datenanalyse und -aufbereitung, Reporting