Duties: This project will focus on the development of a computational infrastructure for the analysis of the exome of patients affected by rare disease. The aims of the project consist in the evaluation of the computational methods for predicting the impact of genetic variants on protein function and gene expression. Such methods are based on the integration of different information related to the networks of protein-protein interaction and genes involved in the insurgence or rare diseases, with particular focus on the intellectual disabilities associated to neurodevelopmental disorders. The final aim of the project consists in the development of a computational platform for the automatic analysis of the genetic variants and the gene expression levels in individuals to estimate the risk of developing a specific class of diseases. The project rely on the financial support of the project PNRRMR1-2022-12376067 “Multiomic strategies to implement the diagnostic workflow of rare diseases”
Requirements: Early stage researcher or 0-4 yrs (Post graduate)

Duties: We are seeking an outstanding candidate for a Lectureship in broadly interpreted Optimisation for Machine Learning and AI within the School of Mathematical Sciences at the University of Southampton
Requirements: a doctorate and postdoctoral experience in a relevant discipline; ability to obtain peer-reviewed funding; evidence of distinction in research through high-quality publications; ability for undergraduate and postgraduate teaching

Department: Medical Sciences; Medicine
Duties: The position is related to research activities in the field of human nutrition, in particular to the use of advanced; biostatistics approaches to study the impact of the diet on human health, in particular dietary patterns characterised by; a high consumption of secondary compounds like polyphenols
Requirements: Early stage researcher or 0-4 yrs (Post graduate)

Duties: The successful candidates will work at the machine learning group at UiT and will formally be affiliated with the Department of Mathematics and Statistics and collaborate closely with researchers at the Department of Geosciences at UiT. The candidate will also interact with researchers in Visual intelligence (a center for research-driven innovation focusing on novel deep learning-based solutions for complex image analysis) and Integreat (a center of excellence focusing on combining statistics, logic, and machine learning to contribute to more knowledgedriven machine learning)
Requirements: This position requires a Norwegian master’s degree in physics, mathematics/statistics, computer science, or similar, or a corresponding foreign master’s degree recognized as equivalent to a Norwegian master’s degree; Experience in signal and image processing; A solid background in machine learning, statistics, mathematics, and linear algebra; Excellent programming skills

Duties: The overall aim of the project is to identify new drug targets/drugs for glioblastoma (GBM), the most malignant and most frequent primary brain tumor, by combining breakthrough technologies from machine learning (ML), bioinformatics, single cell and spatial transcriptomics, organoids, and biotechnology. The person appointed on this position will use causal inference and ML algorithms to identify causal gene regulatory networks in GBM long-term survivors compared to short-term survivors and link these networks to specific tumor/stromal subpopulations by screening single cell/spatial transcriptomics data
Requirements: Applicants must hold a master's degree or equivalent education in informatics, machine learning, bioinformatics, or related discipline, with several years of experience in a research environment; Experience with causal inference is a requirement; Experience with machine learning is a requirement; Experience of programming in at least one programming language is a requirement (Julia, Python, C, C++)

Duties: Our Mission Award proposal aims to utilise Engineering Biology approaches for the development of transferable strategies to engineer antibiotic-producing Streptomyces bacteria able to use a wide range of sustainable feedstocks for production of drug molecules. To deliver this mission we will integrate ‘wet ’and ‘dry ’laboratory data from an authentic industrial Streptomyces strain lineage. We will determine how the strain improvement process has driven strains to adapt to specific media and fermentation conditions and then use this information to build, design and test appropriate engineering strategies for the development and construction of Streptomyces strains that use greener carbon sources. This will ultimately enable us to learn how to rationally design of strains for greener manufacturing and make this strategy broadly applicable to other industrial Streptomyces
Requirements: We are looking for a Research Fellow with expertise in metabolic modelling and computational biology and their application for the analysis of metabolism and the design of strategies for improving the properties of microbial strains. The appointed researcher will design and construct metabolic models based on the information collected from multi-omics experiments carried out by the collaborators, and suggest and propose experiments to select the best producing species and test their performance under diverse culture conditions

Duties: The university offers support of academics from a broad range of career paths, whether you are an established academic who currently holds an equivalent position, or a successful academic seeking an opportunity to grow into a more senior role, this is the place to do something truly unique with your expertise. You will have experience in bioinformatics, epidemiology, systems biology, large-scale ‘Omics data analysis, human centric artificial intelligence, machine learning or large data management. We are seeking candidates whose expertise spans these backgrounds with a track record and demonstrated curiosity for interdisciplinary research
Requirements: To apply, you will need a PhD, or equivalent professional qualifications, with a strong publication record, and able to demonstrate delivery of teaching in a manner that meaningfully engages students. You will have a track record of innovative research in one or more of the following: Computer Science, Health Data Science, Health Research Method Development and Analysis, Bioinformatics, Epidemiology, Public Health, large-scale ‘Omics data analysis, or systems biology; and have a desire to build a strong interdisciplinary research team with the support Medicine and ECS

Duties: You will produce high quality research outputs and contribute to writing competitive grant funding applications in relation to vasculitis and genetic epidemiology. You will also have an opportunity to supervise postgraduate research students undertaking work in this area
Requirements: Applicants will have an MSc or other higher degree in epidemiology, statistics or a related analytical subject or equivalent experience of working in an applied health research or basic science environment. Knowledge and working experience of advanced statistical techniques in medical research are essential while experience of the analysis of germline genetic data would be beneficial

Duties: As a postdoctoral researcher, your key duty is to develop computational solutions to generate high-dimensional synthetic cohorts, consisting of simulated biomarker and imaging data from patients with neurodegenerative diseases, as well as healthy older people. You will be using generative machine learning models, which may include different approaches of generative deep learning (e.g., generative adversarial networks and diffusion-based transformers). When successful, the synthesis will result in cohorts that recapitulate the original data set’s associations between multimodal features (e.g., biochemical markers, neuroimaging, cognitive testing, proteomics, and genomics), but also allow for reproducible discoveries. Additionally, the generation of synthetic data should preserve patient integrity and privacy in a way that allows for flexible and rapid sharing of the synthetic data between researchers and labs
Requirements: PhD degree in engineering, bioinformatics, statistics, computer science, mathematics, computational biology, or a related discipline. This requirement needs to be met no later than when the employment decision is made. Therefore, we also welcome applicants whose PhD degree will be completed imminently; Advanced programming skills, e.g., in R or Python; Good knowledge of machine learning, generative modelling and deep learning; Good knowledge of parallelized computing and use of computer clusters; Good knowledge of oral and written communication in English

Duties: master policy rerating tools and use them to produce estimated quotes for BOP and other small business commercial lines; gain knowledge of internal and external data sources relevant to rating insurance policies and understand the contents and limitations of each; recommend approaches to estimating policy characteristics in the absence of verified policy data; explore new data sources as they become available and document the contents and limitations of each; communicate with business partners about their needs and expectations
Requirements: advanced degree in statistics, mathematics, economics, actuarial science, or other related fields; graduate degree or Ph.D. is preferred; at least three years of property/casualty actuarial experience; proficiency with Microsoft® Excel; experience with VBA, SQL, SAS, R and/or Python

Duties: Subject matter authority in the key model risk area and other related modeling areas; Responsible for managing and executing model validation activities, including validation, annual review, ongoing monitoring, findings management, and model use approvals for low-, moderate-, or high-risk models; Leads a team of junior quantitative model validators to test and evaluate the conceptual soundness of models and assess limitations and suitability for use; Subject matter expert in a key model risk area such as Artificial Intelligence/Machine Learnings, Statistical and Stochastic processes, Finance/Banking/Econometrics or Insurance and Actuarial Modeling
Requirements: Bachelor’s degree in Actuarial Science, Data Science, Mathematics, Financial Engineering, Economics, or another analytical field of study is required; Fellow of the Society of Actuaries (FSA), or Associate of the Society of Actuaries (ASA) with a minimum of 10 years of experience post-ASA, is required; Significant recent experience in actuarial model design, product development, implementation, testing and/or validation is required; Deepen understanding of the models, products, assumptions, and processes across different areas (Life Insurance/Annuity/Health, Inforce/New Business, ALM, Hedging)

Workload: 100%
Duties: Partner closely with Valuation, Assumptions, Accounting Policy, Pricing and Risk Management teams in the development of sustainable annuity projection models, compliant with emerging accounting and regulatory frameworks; Implement processes, infrastructure, and controls to ensure accurate and timely delivery of Annuity projection models and results; Examples of model development work include, but are not limited to: US GAAP including LDTI; VA Statutory and Capital; Economic Valuation and Economic Capital; Implementing, quantifying and reviewing assumption and model updates; Finance Modernization initiatives to improve processes, controls, and analytics
Requirements: Bachelor’s degree in Mathematics, Statistics and/or Actuarial Science; ASA Designation; 2+ years of modeling, valuation and/or pricing experience; Knowledge of annuity products; Experience building and improving actuarial models (AXIS preferred)

Duties: The purpose of this role is to drive performance across our functions in line with our plans for profitable growth. You’ll play a pivotal role in setting our pricing strategy, setting plan targets and working with the business to deliver to these targets. This is a high priority role, you will collaborate and build relationships throughout Finance, Underwriting and the wider business, preparing and communicating key information to senior stakeholders. You’ll manage Unum’s active product portfolio, recommending dynamic pricing actions to optimise profitable growth across our products. You will be commercially minded, ensuring our pricing approach is aligned to our wider strategic goals, while also developing our pricing MI to better utilise available data and deliver meaningful insights
Requirements: Qualified actuary (preferred); Experience in commercial pricing within the insurance industry; Detailed knowledge of the life and/or general insurance industry; Strong communication and interpersonal skills, with the ability to lead relationships with other teams and produce clear and concise reports; The ability to work under pressure, deliver expected results and managing competing and conflicting demands within the workload

Duties: Lead all stages of Data, analytics & AI product development life cycle: from problem identification, conceptualization, prioritization to solution development and delivery; Contribute to hands-on development of data & analytics solutions; Collaborate with business and technology partners to co-create solutions anchored on customer care, human-centered design, frictionless services, and meaningful engagement; Develop Data and Analytics roadmaps. Deliver solutions with transformational impact to the Enterprise; Communicate, engage, and present roadmaps, use cases, solutions and impact to senior management; Deliver products and solutions in a timely, proactive, and entrepreneurial manner; Institutionalize best practices, contribute to research and experimentation efforts
Requirements: Bachelor’s/Master’s degree in an information technology/computer science or relevant domain. MBA or financial services industry experience preferred; 10-14+ years of relevant experience in data and analytics product & solution delivery; Traditional as well as modern statistical and machine learning techniques; Azure ML, OpenAI, Python, PyTorch, SQL, and TensorFlow; Experience working with large and complex internal, external, structured and unstructured datasets

Duties: Possesses a level of versatility to learn new lines of business, balance multiple projects, and a desire to develop and grow within this role; Ability to cultivate relationships between the actuarial/analytics unit and other functional support units within the organization through collaboration and communication; Develops tools to measure and monitor profitability by business unit and product; Identifies trends in claim frequency and claim severity; Creates reports to measure and monitor rate, action-taken, and its impact on retention and new business growth; Develops and maintains a capital allocation model to measure the risk-adjusted performance of each business unit
Requirements: Requires a Bachelor’s degree and at least five years of actuarial work experience or equivalent; Equivalent is considered nine years of actuarial work experience; Must have a solid background in the P&C commercial insurance space, including familiarity with ISO forms/rules. Eager to learn new lines of business and strong desire to be part of a team; Ability to self-motivate and drive to succeed, prior experience of demonstrated goal achievement required, and extensive knowledge of the insurance industry

Duties: Work closely with CI management to set priorities for Benchmarq and other new rating plans; Manage the Benchmarq Rating Plans & Systems team including setting the staff’s priorities/workloads and training/developing; Work with CI management to develop/revise rating algorithms, including providing actuarial rate filing support for state regulators; Collaborate with various stakeholders including IT, Product Services, and Business Analysts to continuously update, maintain, and document the implementation of our rating algorithms; including our rating externalization initiative
Requirements: Bachelor’s degree or higher in a quantitative field such as Mathematics, Actuarial Science, Statistics, Finance, Economics, or a related field; 8+ years of actuarial pricing or reserving experience, or a combination of relevant industry experience and technical skills; ACAS or FCAS certification preferred, or equivalent industry qualifications

Duties: Accountable for multiple projects, providing leadership and advising project teams and statistical leads by challenging statistical design, analysis and decision-making issues; Provides expert opinions, advises staff on available statistical methodologies, performs/supervises modeling and simulations, and leverages external experts to provide input to clinical development issues; Provides oversight on statistical matters for meetings with regulatory authorities, key opinion leaders and similar experts
Requirements: PhD or M.S in Biostatistics, Statistics or related scientific field; 2+ years of demonstrated experience in working on global clinical studies and projects or global process and system initiatives; Knowledge and skills in SAS required, knowledge of R preferred

Duties: Conducts advanced scientific and operational statistical work for multiple clinical trials, observational studies, or real world data (RWD) investigations, including the design, development and execution of the technical/statistical infrastructure; Possesses an advanced understanding of modern drug discovery and development processes; Represents Biostatistics as a member of clinical trial teams, providing input and technical guidance to elicit meaningful and/or productive outcomes; With minimal guidance, authors study Statistical Analysis Plans (SAPs), including table, figure, and listing (TFL) shells. Develops Cross-functional Data Review (xFDR) plan, Key Reports Memo (KRM), and Data Dissemination Plan (DDP) to facilitate the review, summary, and dissemination of key study data/results; Collaborates with statistical programming and other functions to ensure timely delivery of TFLs with good quality
Requirements: Ph. D. or master's degree in Statistics or Biostatistics; Typically requires 3 years of experience with a Ph.D. or 6 years of experience with a master's degree, or the equivalent combination of education and experience

Duties: Exagen Inc. is seeking a dynamic leader in computational biology and data analytics to helm our endeavors in diagnostic testing within the realm of autoimmune diseases. As a trailblazer in the biotech sector and bolstered by our status as a publicly traded entity, our ambition is to craft a comprehensive bio-computing infrastructure. This endeavor aims to harness the vast potential of extensive clinical datasets alongside AI, paving the way from diagnostic breakthroughs to therapeutic innovations. The role of the Senior Director of Bioinformatics & Data Analytics is pivotal, tasked with sculpting the bioinformatics blueprint essential for groundbreaking target discovery and translational science endeavors. In this capacity, you will orchestrate a team of exceptional bioinformaticians and biostatisticians, steering efforts in target identification, biomarker unveiling, and patient stratification
Requirements: PhD in Bioinformatics, Computational Biology, Statistics, Computer Science, or a related field; At least 8 years of post-graduate experience in bioinformatics or computational biology, with a proven track record in the biotechnology or pharmaceutical industry

Duties: Responsible for projects managed by our FSP partners per Amgen Global Statistical Programming (GSP) Quality Oversight Plan (QOP); Ensure that FSP programming meets quality, compliance, timeline, and productivity expectations; Align FSP assignments with Amgen Development priorities; Responsible for FSP performance metrics development, data collection, and reporting and lead the GSP continuous improvement initiatives
Requirements: Bachelors degree or equivalent in Computer Science, Statistics, Mathematics, Life Sciences or other relevant scientific subject; Extensive SAS programming and reporting experience including SAS Base, Macro, STAT, Graph, and SQL, among others; Detailed understanding of clinical trial processes in the biopharmaceutical industry, from data collection to analysis reporting; Ability to lead programmers in successful completion of all study programming activities and provide mentorship on technical and process related questions

Duties: Implements and develops computational analysis pipelines for spatial transcriptomics data and other new kinds of spatial data, implements and develops image analysis software for analyzing microscope images, and produces graphs and data presentations; Utilizes high-performance local and cloud-based computational resources to set up and run custom data analysis pipelines; Works closely with a team of scientists on cutting-edge cardiac biology and neuroscience research projects; Documents code and assists other scientists with analysis; Exercises judgment within defined procedures and practices to determine appropriate action; Performs other related duties as assigned by management
Requirements: B.S. degree in computer science, bioinformatics, computational biology, bioengineering, mathematics, statistics, or related discipline; 4+ years of professional experience in a scientific role in a relevant field (graduate studies included); Advanced Python coding skills

Duties: The Senior Statistical Manager supports the design, execution, analysis, interpretation, and reporting of clinical trials as well as communication of data evidence for Clinical Research & Development and Medical Affairs programs with minimal supervision. This position supports statistical aspects of business-critical and/or regulatory commitments, provides input to program plans with limited supervision, and represents the Clinical Biostatistics function for cross-functional and intra-departmental teams or working groups
Requirements: MS/PhD or equivalent in a statistical discipline with 2-5+ years of experience in relevant technical area; Experience in statistical analysis, modelling and simulation and adaptive trial designs; Experience in working with clinical trials; Preferred experience with oncology clinical trials; Proficient programming skills in statistical software’s, such as SAS

Duties: Develop and optimize analysis workflows to analyze NGS data, including both whole genome sequencing (WGS/WES), targeted sequencing, and bulk/single cell RNA Seq; Develop novel Bioinformatics methods to answer platform and biological questions, and demonstrate validity of methods through prototypes and benchmarking using appropriate controls; Work with other computational biologists and computational engineers to deliver and optimize production-level pipelines; Proper documentation of code, workflows, and analyses including study reports for nonclinical and clinical studies and regulatory filings; Communicate to a broad audience with a range of technical, analytical, and biological expertise and present results on a regular basis at various group meetings
Requirements: A PhD and 3+ years post-PhD experience in bioinformatics, computational biology, and data science; Demonstrated experience in the field of computational biology, CRISPR off target genomics, cancer genomics, and/or single-cell genomics; Extensive expertise in analyzing, interpreting, and visualizing human genomics datasets generated by high-throughput sequencing technologies including short- (Illumina) and long-read- (e.g. PacBio and Oxford Nanopore) sequencing; Extensive experience performing statistical analyses of large genomic datasets and validation of genomic pipelines; Expert-level proficiency in relevant programming languages such as R and Python; Proficiency in tools for ensuring reproducibility of pipelines, such as workflow management systems (e.g., nextflow or snakemake), and version control (e.g., git)

Duties: Establish dedicated analysis and informatics to support company milestones; Support internal R&D projects and Product Development; Develop, implement and troubleshoot novel analysis tools for SBS/ZMW/nanopore-based raw data and sequencing data; Support all science teams through the development of systems for streamlined data acquisition and collaborate with colleagues to create specific analysis pipelines that address team needs; Automate data analysis pipelines, maintain SOPs for multi-team use, and provide troubleshooting support as needed; Maintain a centralized, shared and organized historical records of experiments conducted, problems solved, and bugs fixed; Generate professional reports and visuals on performed data analysis, developed tools, and approaches, playing a critical role in the development of internal processes and eventual customer applications
Requirements: Ph.D. or M.S. in Bioinformatics, Statistics, Computer Science, Computational Neuroscience or a related field; For Senior Scientist: Ph.D with 4+ years of industry experience; or M.S. with 6+ years of post-graduate experience; For Staff Scientist: Ph.D with 8+ years of industry experience; or M.S. with 12+ years of post-graduate experience; Experience applying signal processing and signal filtering techniques to 1D/2D time-varying data. Eg. Image classification, Audio Signal Processing, digital signal from electronics etc. (Preferred experience with raw imaging data from SBS-style DNA sequencing or raw electrical signal from nanopore sequencers)

Duties: The primary purpose of the Associate Data Scientist is to leverage the capabilities of next-generation sequencing data to drive forward the discovery and development of novel therapeutics for cancer patients. This crucial role is centered on analyzing and interpreting intricate genetic information at the single-cell level to identify unique biomarkers and understand tumor heterogeneity. By crafting advanced computational tools and algorithms, the Associate Data Scientist will play a crucial part in accelerating scientific discoveries and contributing to the development of new therapies and diagnostics that can transform patient care and health outcomes
Requirements: Deep knowledge of bioinformatics tools and their implementation as part of pipelines, particularly for scRNA-Seq, scATAC-Seq, Spatial transcriptomics and/or other multi-dimensional omic data modalities; Demonstrated experience and understanding of genomic technologies and analysis of data generated; Analyzing and interpreting outputs to identify insights and hypotheses from data; Understanding of essential statistical methodologies required for bioinformatics analyses