Department: Division of Psychiatry - Epidemiology & Applied Clinical Research
Workload: part-time
Duties: A statistician or statistically-oriented Epidemiologist is sought whose main role will be to teach statistics and to provide statistical support for research projects for students on the MSc in Clinical Mental Health Sciences and the MSc in Mental Health Sciences Research at UCL’s Division of Psychiatry. We are looking for someone who is an excellent teacher and communicator with strong research skills and an excellent ability to communicate with and support students. They will join an excellent academic team supporting the courses. Student research from our course is often published, and there is potential for the candidate to develop research collaborations with academics in the Division
Requirements: The post holder must hold a higher academic degree e.g. PhD or equivalent in research publications and MSc statistics or with large statistical component e.g. MSc epidemiology; Experience of teaching in higher education and preparing teaching sessions is essential. The successful candidate will have advanced knowledge of the statistics relevant to mental health research. Experience of contributing or leading applications for research funding would be desirable although not essential for this post

Duties: Your contribution will be within control engineering with an emphasis on research, technology implementation and teaching in one or more of the following areas: Autonomous systems; Robotics; Industrial Automation; Mechatronic development; Control Engineering
Requirements: As formal qualifications you must hold an MSc or a PhD degree (or equivalent). If you are applying for the associate professor position, you should also have academic qualifications equivalent to those obtained by holding an assistant professorship and documented didactic/pedagogic training

Workload: part-time
Duties: The postdoc will coordinate research projects and establish new research initiatives in the intersection of forecasting, optimization, and machine learning for flexibility services in transmission and distribution grids. It is envisioned that approaches based on machine learning, optimization, and online control will be developed to handle large datasets and optimization problems in a computationally efficient and reliable way. The Postdoc shall establish contacts with major industry stakeholders in Denmark and Europe in the field of energy flexibility services
Requirements: As a formal qualification, you must hold a PhD degree (or equivalent)

Workload: 80-100%
Duties: Développement des instruments de surveillance basée sur les données et semi-automatisée; Analyse et visualisation des données, en mettant l'accent sur des analyses quantitatives; Participation au développement des outils pour les calculs de solvabilité basés sur des simulations; Participation au suivi des entreprises d'assurance pour des aspects liés au SST. Réponses à des questions liées au SST; Participation au développement continu et à la maintenance des modèles standard ainsi qu'aux outils de surveillance correspondants dans la surveillance des assurance (y compris l'implémentation informatique)
Requirements: Diplôme universitaire avec une formation technique (mathématiques, statistique, data science, informatique, physique); Très bonnes compétences de mise en œuvre informatique; Très bonnes connaissances des bases de données (SQL) et des langages de programmation dans le domaine de l'analyse de données, par ex. R, Python, éventuellement Matlab; De l'expérience dans le traitement et l'analyse de données ainsi que dans la préparation et le reporting des résultats constitue un atout

Duties: Claim reserves review for statutory filings; Actuarial support for due diligence and appraisal value for mergers and acquisitions of non-life insurance companies; Strategic work including reinsurance optimization, risk and capital management, market entry support, etc; Modelling support for IFRS17 implementation; HKRBC implementation support, including statutory filings, capital analysis, ORSA requirements; Portfolio review and risk profile analysis; Actuarial assistance for the development of new general/health products and premium rates; Market research and analysis; Actuarial analytics applied in non-traditional areas
Requirements: Bachelor oder besser in Actuarial Science oder verwandtem Gebiet; 0-2 years of experience related to an area of actuarial work

Duties: Laufende Analyse, Qualitätssicherung und Weiterentwicklung von Konzerndaten, welche in das interne und das externe Berichtswesen einbezogen werden; Ausführung, Qualitätssicherung und Weiterentwicklung der im Einsatz befindlichen SQL-Abfragen, mit dem Ziel der Sicherstellung einer laufenden Fortentwicklung; Mitbegleitung und mittelfristige Übernahme von eigenständigen, fachspezifischen Datenanalyseaufgaben, wobei auch Datensystem- und Datenintegrationstests mitbegleitet werden; Entwicklung von neuen Datenarchitekturen auf Konzernebene, welche für die Umsetzung neuer Datenanforderungen benötigt werden
Requirements: Abgeschlossenes Studium der Wirtschaftsinformatik, Informatik, Mathematik, Statistik oder Bioinformatik oder vergleichbare Ausbildung (IT-HTL, Erfahrung als Datenanalyst); Gute Kenntnisse über Datenbankdesign, Datenmodelle und SQL; Analytisches Denkvermögen und ausgeprägtes Zahlenverständnis; Selbstständige und flexible Arbeitsweise; Teamfähigkeit und Freude in einem eingespielten Team eine langfristige zentrale Aufgabe zu übernehmen

Duties: Mitarbeit bei Projekten zur Herstellung der Abwicklungsfähigkeit und Umsetzung der Abwicklungsinstrumente; ​​Laufende Koordinierung von Datenanforderungen der Aufsichtsbehörden im Haus; Vertretung in nationalen Arbeitsgruppen sowie laufende Abstimmung mit Aufsichtsbehörden (OeNB, FMA, SRB); Prüfung von Verträgen auf BaSAG-Relevanz; Auslegung und Stellungnahmen zu Richtlinienentwürfen und Gesetzestexten
Requirements: Abgeschlossenes Studium (Wirtschaftswissenschaften, -informatik, Betriebswirtschaft, Volkswirtschaft, Rechtswissenschaften); Mehrjährige Berufserfahrung im Bank-, Aufsichts- oder Beratungsumfeld idealerweise im Abwicklungs- oder Sanierungsbereich; Sehr hohe IT- und Zahlenaffinität sowie ausgeprägtes analytisches Denkvermögen; Freude, komplexe Herausforderungen im Team zu lösen; Hoher Grad an Selbstorganisation

Duties: Mitarbeit bei Projekten zur Herstellung der Abwicklungsfähigkeit und Umsetzung der Abwicklungsinstrumente; ​​Laufende Koordinierung von Datenanforderungen der Aufsichtsbehörden im Haus, v.a. die Umsetzung der Datenerfordernisse und der dafür erforderlichen Implementierungsarbeiten; Vertretung in nationalen Arbeitsgruppen sowie laufende Abstimmung mit Aufsichtsbehörden (OeNB, FMA, SRB)
Requirements: Abgeschlossenes Studium (Wirtschaftswissenschaften, -informatik, Betriebswirtschaft, Volkswirtschaft, Statistik); Berufserfahrung im Bank-, Aufsichts- oder Beratungsumfeld von Vorteil; Sehr hohe IT- und Zahlenaffinität, fundierte SQL-Kenntnisse sowie ausgeprägtes analytisches Denkvermögen; Interesse an der Konzipierung und Umsetzung von (Bank)Datenmodellen sowie an der Erweiterung der Datenarchitektur mitzuarbeiten; Hoher Grad an Selbstorganisation

Duties: Einführung und Überarbeitung von Non-Retail-Ratingmodellen sowie deren Servicierung im operativen Betrieb; AnsprechpartnerIn für RatinganalystInnen und ValidierungsmitarbeiterInnen; Zentrale Rolle bei abteilungsübergreifenden Projekten im Zusammenhang mit Ratingmodellen; Kontrolle der Ratingprozesse auf CRR (Kapitaladäquanzverordnung)-Fähigkeit; Begleitung bei internen und externen Kreditrisikoprüfungen; Aufbereitung und Präsentation von Inhalten im Zuge von Gremien, Vorstandssitzungen und im Zusammenhang mit Anfragen der Bankenaufsicht
Requirements: Abgeschlossenes Studium (Wirtschaftswissenschaften, -informatik, Betriebswirtschaft, Volkswirtschaft, Statistik, Mathematik); Einschlägige, mehrjährige Bankerfahrung (vorzugsweise in Rating-/Finanzierungsprozessen); Mathematisches/statistisches, technisches Verständnis und IT-Affinität; Durchsetzungsvermögen, Kommunikationsstärke und Teamfähigkeit

Duties: The successful candidate will help lead efforts to apply computational and new statistical tools to molecular phenotype pipelines for patient characterization and stratification, assist with data analysis, modeling, visualization and interpretation of clinical and experimental data. We have access to an extensive curated electronic clinical research health record and experimental data warehouse already available to be leveraged for these projects. The team utilizes high throughput bimolecular assays, deep cellular phenotyping, and single cell genomic and proteomic methods through our Human Phenotyping Core. We also have access to high performance computational resources both in-house and through cloud-based resources
Requirements: Ph.D. in a biological science, statistics, applied mathematics, epidemiology, chemistry, physics or other relevant area, M.D., or equivalent field and some relevant experience. Must have the ability to perform statistical analysis using appropriate statistical software programs and/or program in R. Must have good organizational and communication skills. Must be able to work independently, as well as highly attentive to detail, and dependable. Works as a team player and perform other duties as assigned by supervisor

Duties: Help design, develop, and support machine learning models, algorithms, statistical models, and other programs designed to improve the public sector; Lead the collection of new data and the refinement of existing data sources. Work withlarge untapped data sets, including: health and environmental enforcement data, mass adjudication records, high-resolution satellite imagery (15cm/pixel), and the largest publicly available corpus of legal text; Implement and interpret the results of new experiments and studies in partnership with government agencies, researchers, non-profits, or other stakeholders; Lead testing, release, and maintenance processes and collaborate with technical staff to standardize and systemize data standards, elements, and metrics
Requirements: A bachelor’s degree in a relevant quantitative field (e.g., data science, computer science, statistics, engineering, mathematics, economics, or a related field) and three years of relevant professional experience or a combination of education and relevant professional experience; Basic knowledge of software engineering principles and strong knowledge of at least one programming language, such as Python, R, and/or SQL); In-depth knowledge and experience using and applying analytical software, database management system software, database reporting software, database user interface and query software, and data mining software; Basic statistical ability

Duties: Propose and conduct highly advanced approaches/experiments using established scientific protocols and procedures and in some cases designing new approaches; Summarize findings and publish results in research journals; Assume general responsibility for scientific operations of the laboratory; Provide supervision and guidance to junior phd students, and researchers; Conduct the research in the area of complex network; Propose new approaches for complex network and develop asymptotic theory for the proposed methods
Requirements: PhD in statistics; Strong interpersonal and communication skills; Familiar with asymptotic theory in probability; Familiar with high dimensional statistics inference; Familiar with R or Matlab

Duties: The Mathematics Department at KFUPM invites applications for faculty positions in the following areas: Real and Complex Analysis; Applied Mathematics; Numerical Analysis; Statistics; Differential Geometry; Probability Theory; Actuarial Science
Requirements: Applicants must have an earned Ph.D. from reputable institution, strong record of published research, experience in supervising research of graduate students, relevant teaching experience at the university level and have teaching and/or industrial experience in the respective areas

Duties: To conduct research on artificial intelligence (AI) - based approach to optimize yield of indoor crops under solid and hydroponic substrates; To actively participate in mentoring of graduate students and research staff; To publish scientific outcomes of the research in high impact, international peer-reviewed journals
Requirements: PhD in Statistic, Mathematics, or a related discipline; An established track record of research and relevant publications in reputable peer-reviewed international journals; A good track record in university teaching/mentoring in related field; Experience in supervision of graduate and undergraduate students; Demonstrated ability to obtain external research grants

Duties: Precise control of gene expression accompanying developmental changes is frequently conferred by distal cisregulatory modules (CRMs), such as enhancers, often acting at large genomic distances from their target gene promoters. Recent evidence supports a model of chromatin loops bringing individual enhancers into contact with activated genes, but this is challenged by recent findings. Imaging experiments have shown enhancers at large distances from activated genes, and large multi-CRM-promoter hubs have been identified, which sometimes (but not always) co-associate with clusters of specific transcription factors (TFs)
Requirements: The candidate is expected to have a strong background in physics, mathematics and programming

Duties: Conduct research in various areas of applied and computational mathematics including applied analysis, mathematical modelling, scientific computation, numerical analysis, probability and statistics etc; teach undergraduate and postgraduate courses; supervise research students; and perform any other duties as assigned
Requirements: A PhD in Mathematics/Applied Mathematics/Statistics with an excellent research record

Duties: Act as lead Statistician for multiple studies; Provide statistical input to the design and review of Protocols and Case Report Forms; Perform sample size calculation and randomization; Prepare Statistical Analysis Plan and specifications documents; Provide support for DMC/DSMB charter preparation and meetings; Participate in the programming, validation and analysis of clinical trials including analysis datasets and TFLs; Participate in the review of clinical data; Interpret statistical analysis results
Requirements: MSc in Biostatistics, Bachelors’ Degree in Biostatistics, Degree from Statistics Schools (ENSAI, ENSAE, ISUP); At least 3 years of experience within the pharmaceutical or biotech industry, research or CRO; Very good knowledge of statistical methodology and regulations applicable to clinical trials; Good knowledge of SAS® (base, macro, stat, graph) or any other programming language; Very good English communication skills, both written and verbal; Very good organisational skills

Duties: TIFAC-CORE in Cyber Security (Coimbatore Campus) and the Center for Cyber Security Systems and Networks (Amritapuri Campus) are well known globally for their pioneering research in cyber security. The centers promote partnerships between industry, academia and the government to foster innovative research and education in cyber security. The centers have openings for Associate Professors on both campuses
Requirements: Ph.D. or M. Tech from reputed universities in the area of Cyber Security/Artificial Intelligence/Computer Science. Fresh graduates are also encouraged to apply; Must have published a minimum of 3 quality papers in SCI or Scopus indexed journals; Research experience in the following areas would be preferred: Cyber Forensics, Malware Analysis, VAPT, Mobile security, Formal Methods, Cryptography, Reverse Engineering, System Security, and Hardware Security

Duties: As a member of a new dedicated IFRS Valuation team, acting as the subject matter expert responsible for the valuation processes underlying the production, analysis, and review of IFRS reserves and related financial information (including Best Estimate Liabilities (BEL), Risk Adjustment (RA) and Contractual Service Margin (CSM)) for Legal & General America (LGA) and affiliated entities
Requirements: BS/BA in Actuarial Science, Mathematics, Statistics, Economics, or related field; Fellow of the Society of Actuaries; 8+ years of life insurance/actuarial experience, including valuation; Experience with IFRS 17

Duties: To work closely with your team and our consultants working across the globe to ensure high quality client deliverables; To help setup internal processes/procedures during the initial phase of the practice; To work effectively in a team of 5-10 members; To help train and motivate colleagues; To deliver diverse range of projects (actuarial modelling, actuarial valuations, pricing reports, market reports and many more types of projects) for practices located in different parts of the world; To help develop and maintain client/internal relationships; May be required to travel overseas
Requirements: Masters or Bachelors degree in a relevant field with a good academic record; 0-1 years of professional experience; Basic actuarial domain knowledge of life and annuity product; Passed one or more actuarial exams; Knowledge of Python, R and SQL will be of additional help; Demonstrable progress through actuarial examinations; A basic understanding of life insurance actuarial concepts; Excellent analytical, software and problem solving skills; Advanced user MS Excel, MS Access and MS PowerPoint

Duties: Milliman is seeking a consultant to join our new life insurance actuarial consulting team in Kuala Lumpur. The candidate can expect to be involved in mergers & acquisitions, risk management, and business/product strategy work in addition to traditional actuarial work. This role will involve exposure to work in Malaysia and other markets around the region and may involve international travel from time to time. A strong focus will be placed on the on-going professional development of associates within an exciting and stimulating working environment, with a view of the candidates taking senior responsibilities in the near future
Requirements: have more than 5 years of work experience in a well-regarded life insurer, reinsurer, or consultancy; have made good progress towards actuarial exams or is newly qualified; have experience in leading or managing teams and/or projects; have had exposure in modelling related work/projects (ideally using Prophet), financial reporting and insurance regulation

Duties: The candidate will spearhead computational analyses for cutting edge projects in the context of Cancer Research (Ovarian Cancer, Thymoma, Glioblastoma Multiforme) and with a strong focus on organoid-based disease modelling and single cell multiomics. S/he will work in close interaction with wet lab biologists in the analysis of a diverse array of omics data, from the experimental design to the subsequent downstream analyses and including the development of new computational pipelines aimed at the integration of different omics sources
Requirements: PhD in Computational Biology, Systems Biology, Data Sciences or equivalent; Strong knowledge in either Python or R programming; Knowledge of UNIX environment and bash scripting; Familiarity with code versioning systems (e.g. git); Proven expertise in handling omics data (from QC to downstream analysis) on at least two of the following: single-cell RNASeq, single-cell ATACSeq, Bulk RNASeq, ChiPSeq, DNASeq (Whole Genome, Whole Exome, Targeted Resequencing), Methylation Arrays

Duration: 2 y
Duties: Meeting faculty members and researchers to evaluate their bioinformatics needs; Conducting data analysis that meets quality standards of major peer-reviewed publications; Providing faculty members and researchers with data, analysis protocols, figures, method descriptions, code, documentation, support, and anything else that might be needed to meet project goals; Managing time and projects efficiently to support the analysis needs of multiple labs simultaneously; Establishing, refining, and standardizing the process for bioinformatics analysis and validation. Benchmark-driven development is expected, e.g., use of PrecisionFDA/Genome-in-a-Bottle for DNA-Seq analysis, or the use of well-characterized data or simulated data where commonly-used reference datasets do not exist
Requirements: PhD in Bioinformatics, Computational Biology, Physics, Computer Science or related field; Ability to define and solve logical problems for highly technical applications; Deep understanding of next-generation sequencing data and bioinformatics algorithms. While Illumina sequencers are the most common data source, it is not unusual to see 10xGenomics or PacBio data; Provide best-practices data analysis, including QC and visualization, employing common NGS pipelines such as RNA-seq, ChIP-seq, ATAC-seq, Methyl-seq, DNA-seq, and Microbiome Sequencing. Multi-omics analysis is often needed; Proven experience working in a Linux cluster environment. Experience in cloud environments is also a plus

Duties: Bei uns startest Du in einem jungen, dynamischen Team mit spannenden versicherungsmathematischen Projekten in das Berufsleben; Vielfältige Aufgabengebiete, auch in den Bereichen Data Science und Analytics, bieten Dir Abwechslung und helfen beim Aufbau einer breitgefächerten Berufserfahrung; Wir fördern gern Deine Weiterbildung, z.B. zum Aktuar (DAV); Du knüpfst Kontakte bei namhaften Kunden, lernst verschiedenste Unternehmen und Orte in ganz Deutschland kennen; Unsere flache Hierarchie, kurze Entscheidungswege, attraktive Vertragsgestaltung und flexible Arbeitsplätze bieten Dir eine entwicklungsfähige Perspektive
Requirements: Den Hochschulabschluss in Mathematik hast Du (bald) in der Tasche; Versicherungsmathematik interessiert Dich brennend. (Lebens-)versicherungsmathematisches Wissen hast Du Dir vielleicht schon angeeignet. Auch für Analytics und IT kannst Du Dich begeistern; Programmierkenntnisse in APL, Python, R, C#, Visual Basic oder C stehen auf Deiner Haben-Seite; Teamfähigkeit und analytisches Denken zeichnen Dich besonders aus. Eine selbständige, sorgfältige und strukturierte Arbeitsweise ist für Dich selbstverständlich; Du bist kommunikationsstark, arbeitest kundenorientiert und freust Dich auf deutschlandweite Projekte

Duties: Candidates with expertise in one or more of the following areas: Advanced Probability, Advanced Mathematical Statistics, Regression Analysis, Multivariate Analysis, Categorical Data Analysis, Optimization, Time Series Analysis, Survival Analysis, Actuarial Mathematics, Data Mining and Bayesian Statistics are welcome. We are particularly interested in applicants whose research is in the field of applied statistics, data science, machine learning, deep learning or actuarial mathematics
Requirements: Candidates should have a PhD degree in a related discipline. Proficiency required in one or more of analytical tools such as R, Python, Matlab, or SAS. Successful candidates are expected to be committed to excellence in undergraduate or postgraduate teaching. Preference will be given to candidates who can undertake independent research leading to outstanding outcomes, including publications in high quality international-refereed journals.Research experience on Statistical modeling (Regression, Classification, Time-series forecasting)/Machine Learning/Deep Learning/Text Mining/Optimization/Visualization are desirable. Academic rank will be determined in accordance with successful candidate’s experience and accomplishments