Duties: Assisting in the development of all the research activities in a predefined topic and producing results; Providing support in setting-up and running experiments; Proposing and implementing real-time solutions; Participating in organizing relevant workshops and demonstrations; Assist on the laboratory setup preparation and experiment configuration
Requirements: A bachelor degree in Electrical Engineering, Computer Science, Applied Mathematics or a related field; Extensive experience working in different industrial domains; Experience working with cross-functional teams of data scientists, user researchers, product managers, designers, and engineers; Experience managing data and AI programs for schools; Strong background in image/signal processing and in particular; Performed analysis on large sets of data to extract impactful insights; Strong programming skills in Python/C/C++

Duties: Develop theoretical and methodological framework for the value of travel time estimation considering automated vehicles impacts; Design original best-worst scaling experiments and stated preference choice experiments; design questionnaires and collaborate with LISER’s survey team; Analyze the survey data; Develop models for the adoption of emerging modes using hybrid choice modeling approaches; Collaborate with the project partner at TUM and write academic papers and present the results in national/international conferences
Requirements: Ph.D. degree in transport planning/economics/engineering, or other relevant field; Excellent knowledge in discrete choice behavior modeling/travel behavior modeling/stated preference survey design; Good skills and experience in data analysis using statistical software; Excellent communication and collaboration skills; Fluency in English (speaking and writing), any other language is considered as an asset

Duties: The GNSS-R Satellite Earth Observation (GLITTER) project harnesses the power of GNSS-R (Global Navigation Satellite System-Reflectometry) for advanced Earth observation. This technique uses the reflections of GNSS signals off various surfaces - land, sea, and ice - to monitor environmental conditions. Our ambitious goal is to pioneer a new generation of experts capable of making significant advancements in this field through doctoral level education and research. At the heart of GLITTER is the development of a synchronized constellation of CubeSats, offering a cost-effective yet powerful approach to Earth observation. This innovative system allows for enhanced resolution and data accuracy through advanced beamforming techniques. Essential to our methodology are ground-truth data and calibration methods derived from near-field radar technology, which will enable comprehensive research across all facets of GNSS-R technology
Requirements: A master’s degree or equivalent in geodesy, geophysics, remote sensing, applied mathematics or physics, computer science, telecommunication engineering with a focus on remote sensing and EO, or similar; Knowledge of remote sensing techniques preferably radar techniques; ideally experience in analyzing GNSS or EO data; Strong programming skills in MATLAB, Python or C++; Highly committed, excellent team-worker, and strong critical thinking; Excellent written and verbal communication skills in English

Duties: This PhD project aims at the development of an improved distributed control of such formations of small satellites, also using a combination of solar and aerodynamic forces for propellant-less control. This will be ideal to deploy, maintain and reconfigure cost-efficiently a large formation of small satellites but requires the detailed modelling of the satellite dynamics, including the effects of aerodynamic forces (caused by the residual atmosphere in LEO) and the solar radiation pressure. After an analysis of optimal formation geometries for Earth observation, suitable orbital guidance and attitude control approaches will be developed and tested, using advanced simulation tools as well as formation flight experiments on a smaller scale with drones. These flight tests will also provide a better understanding of the level of control needed to achieve satisfactory beamforming
Requirements: The candidate should possess an MSc degree or equivalent in Control/Aerospace/Electrical Engineering, or related fields in Engineering or Computer Engineering. Solid experience/knowledge in the following areas: Mathematical and Control Engineering, especially related to spacecraft guidance; navigation and control; Modeling and simulation of spacecraft dynamics; Spacecraft formations/swarms; Control of drones and flight experiments as well as knowledge in GNSS would be an asset

Duties: The specific duties for this position may include protocol development, study design, analysis plan, sample size/power calculations, and interpretation of study data; develop, design and write new and/or revised statistical programs (say in SAS or R) and modeling based on requirements of ongoing research projects; conduct and interpret analyses of research data using descriptive statistics, inferential tests, and advanced statistical methods and models; evaluate and ensure statistical integrity, accuracy and validity of research data; compiles results and provides statistical summaries and reports to principal investigators; assist with grant proposal preparation in study design, sample size calculations, and development of statistical analysis plans; assist with preparation of journal articles, technical reports and other materials for publication and presentation; manage biomedical databases for assigned research projects; read and review appropriate biomedical and statistical papers...
Requirements: Master's degree in biostatistics, statistics or related quantitative field with 6+ years’ experience in design, conduct, monitoring, and analysis of cancer clinical studies, in preparing and reviewing clinical trial protocols, and in preparing grant applications and writing research reports, or doctoral degree with 3+ years’ experience in these areas

Duties: Be responsible for leading the research culture at PMU. The focus of the job will involve own research activities in area of expertise in AI in addition to presenting research findings at conferences worldwide; Seek external funding to support and expand research activities to enhance the prestige and visibility of PMU and to initiate research projects with local industries, government agencies and the community; Be expected to take part in the strategic planning and decision making of PMU’s Center for Artificial Intelligence
Requirements: A PhD degree in computer science, engineering, physics, data science, mathematics or a closely related field; A proven track record of carrying out cutting-edge research demonstrated by publications in top journals/conferences; A proven track record of funding acquisition through grants and/or contracts; Excellent written and verbal communication skills

Duties: The appointees are expected to make significant contribution to teaching at both undergraduate and postgraduate levels; advise postgraduate research students; play an active role in curriculum development and management; maintain an active research profile; actively seek external grants and contracts to support research endeavours; provide service to the School and University governance; contribute to professional engagement, networking, and outreach activities that enhance the academic and professional life of the School
Requirements: A PhD in Data Science/Statistics/Computer Science/Engineering or related disciplines, with a strong research record and promising teaching ability

Duties: Shaping research directions and producing results. Topics include but are not limited to: Deep learning models suitable for deployment on edge devices (e.g., NVIDIA Jetson, FPGA, etc.); Neural Architecture Search (NAS) for minimal deep architectural design; Efficient in-orbit object pose estimation and tracking; Disseminating results through scientific publications; Providing guidance to PhD and MSc students; Providing support in setting up and running experiments in the SnT Computer Vision and the Zero-G labs; Participating in organizing relevant workshops and demonstrations; Participating to teaching activities
Requirements: A PhD degree in Electrical Engineering, Computer Science, Applied Mathematics or a related field; Competitive research record in Computer Vision, preferably with publications at top-tier CV/ML conferences/journals (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, TPAMI, etc.); Broad experience with machine learning algorithms and deep learning concepts; Highly experienced in one or more of the following topics: Efficient deep learning; Neural Architecture Search (NAS); Embedded systems; Jetson-Nano and/or FPGA deployment; Object pose estimation and tracking

Duties: One year appointment teaching all levels of mathematics courses and/or statistics courses. Duties include 12 hours of teaching each Fall and Spring semester totaling 24 hours of teaching per academic year. Courses will be made up of 3 and/or 4 credit hour courses. One year appointment with possible reappointment, pending funding and evaluations
Requirements: Candidates should have a Ph.D. in Mathematics or closely related field. Applicants from all areas of mathematics are encouraged to apply

Duties: Teaching, research, and service responsibilities in the area of applied mathematics and statistics
Requirements: Ph.D. in mathematics, statistics, or a related field

Duties: Post-Doctoral Fellow (A or B) with PhD in Multi-Object Tracking and Robotics
Requirements: PhD (or soon to be awarded) or equivalent industry experience in; Robotics; Signal Processing/Control; Path Planning/Trajectory Planning; Multi-Target Tracking/Multi-Object Tracking; Bayesian Filtering, Radom Finite Set filters or closely related multi-target tracking approaches; NeRF

Duties: Provide independent statistical support to Neurosurgery research projects, demonstrating expertise in biostatistics, statistical analysis software, and relevant clinical research methods. Collaborate with multidisciplinary teams to design and implement statistical models, manage databases, and ensure effective communication of statistical concepts to non-statistical audiences; Critically evaluate statistical analysis plans for clinical trials and epidemiological studies, propose plans, and conduct sample size calculations. Prepare datasets for analysis by cleaning, merging, and reformatting data. Utilize SAS and/or R for statistical data analysis, computation, and programming
Requirements: A PhD in Biostatistics, Statistics, Epidemiology or related field is required, plus a minimum of three (3) years’ work experience in biomedical research in academia, government, or industry

Duties: Owning and leading various projects, serving as a subject matter expert; Developing and implementing bioinformatics tools and pipelines in cloud environment; Collaborating with DFCI software engineering and data science teams as well as interacting with external cloud and other technology vendors; Meeting, consulting, and providing computational and informatics support to various DFCI scientists and independent faculty members in designing and executing key biomedical projects; Collecting, analyzing, interpreting, and integrating complex biomedical data; Delivering results for projects and generating relevant reports
Requirements: Bachelor’s degree required in a STEM field. Master’s degree or PhD strongly preferred in bioinformatics, medical informatics, computational biology, statistics, computer science/engineering, or a related quantitative field; Deep bioinformatics skills at the interface between bioinformatics programming and understanding of biological and clinical problems

Duties: Work on unique, multi-omics datasets to support translational lung cancer metabolism research; Develop cutting-edge methods for processing, analyzing, and interpreting multi-omics data; Enjoy a close working relationship with bioinformaticians, statisticians, bench scientists, and translational researchers to establish a well-rounded multidisciplinary team; Join an institute that highly values computational research
Requirements: PhD in Bioinformatics, Data Science, Computational Biology, Machine Learning, Statistics/Biostatistics, or related fields; Experience working with at least one “omics” type (e.g., DNA-seq, RNA-seq, metabolomics, proteomics); Preference will be given to candidates with experience in integration of multi-omics data; Programming experience in statistical program R and/or scripting languages such as Python/Perl on Unix/Linux systems; Highly motivated and independent researcher with a background in cancer biology; Excellent communication and writing skills

Duties: The Wistar Institute has an opening for a motived candidate to join the Bin Tian lab as a Post-Doctoral Fellow to study regulation of mRNA processing and metabolism in cancer using computational and bioinformatic approaches. One area of our research is to examine how dysregulation of mRNA processing steps, especially the 3' end processing, impacts mRNA metabolism, such as subcellular localization and translation, and helps cancer cell survival and metastasis
Requirements: Candidates should have a Ph.D. degree in Computational Biology, Bioinformatics or a related field. Candidates who have experience in experimental biology and wish to advance a career in Bioinformatics and Computational Biology are also encouraged to apply. The successful candidate is expected to have good communication skills that are necessary for effective collaborations

Duties: We are searching for an outstanding Bioinformatics Engineer with an interest in working closely with computational biologists and experimental biologists to deploy bioinformatic methods and resources relevant to single-cell sequencing and spatial imaging. The focus of this work is the building and maintenance of software tools, pipelines, and resources for integrative analysis of high throughput sequencing and imaging data
Requirements: A PhD degree or equivalent experience in biological sciences, mathematics, physics, bioinformatics, or related discipline with a quantitative background; Knowledge of sequencing and imaging technologies and their application; Proven experience with computational tools and workflows for the analysis of genomic datasets; Strong programming skills and proficiency in scientific computing software and scripting languages such as Python and R

Duties: Use AWS to provide serverless and cutting-edge ML solutions; Contribute to leading both research and clinical initiatives to develop software solutions for complex data science projects; Use software design and development best practices to create and maintain efficient data analysis and workflow pipelines; Employ best practices in coding, including thorough testing and documentation of code
Requirements: Bachelor's or Master’s degree in computer science, electrical engineering, or related discipline; AWS certification is a plus; Three to five years of programming experience; three to five years of systems experience; minimum of two years of application development experience in a clinical and/or research setting

Duties: The Biostatistician I is the entry-level position of the biostatistics career ladder. The role largely works under close supervision of teams that include a more senior statistician/manager and one or more biomedical domain experts. Management of this role is usually provided on a daily basis with emphasis on proper procedures and technical issues; Consults with team members to determine study design, conduct power calculations, identify appropriate variables and methods, format data, and identify and resolve data anomalies; Operates according to a statistical analysis plan that includes methods, programming procedures, variable definition, and data handling rules and procedures
Requirements: Bachelor's Degree; Previous experience with progressively more complex applied statistics; Previous applied experience in using one or more common statistical language programs

Duties: Creates design and construction of databases for the purpose of research projects and clinical trials. Monitors and coordinates data collection and provide critical feedback for improvement. Conducts statistical analyses for the use in reports, presentations and manuscripts. Provides advisory services in the use and interpretation of statistical analyses on research projects, clinical trials, grants, proposals, and consultation services
Requirements: Bachelor’s degree in Statistics/Computer Science/Bioinformatics/Data Specification/Data Science/Computational or equivalent experience. 3-5 years of experience in Statistics/Computer Science/Bioinformatics/Data Specification/Data Science

Workload: 100%
Duties: Help our diverse community of scientists in using our computing infrastructure and collaborate within the team to guarantee smooth operations of the environment; Contribute to the configuration and maintenance of the HPC and virtualization environments, and adapt it to the current needs of the research community, following our Infrastructure-as-Code approach; Collaborate with the implementation of security measures, user workspaces, and services in our biomedical IT research environment (sciCOREmed); Contribute to the general Linux operations of the service, depending on interest and skills (storage management, software deployment, support for web applications, IT security); Participate in relevant technical meetings with our partners at the University of Basel and at SIB - Swiss Institute of Bioinformatics
Requirements: Masters in computer sciences or equivalent, or academic degree in a computational domain; Ability to work collaboratively in service operations based on agile and four-eyes principles; Strong experience with Linux systems administration, preferably in an HPC-based research environment; Hands-on experience in configuring, deploying, and supporting web services: incl. application and management services (e.g. access control, monitoring, logging); Hands-on experience with script-based system management (bash, Python) and in using version control systems for configuration management (e.g. git); Knowledge of Linux configuration tools such as Ansible, Terraform, MAAS

Duration: 20 m
Duties: The project will study male-female health differences with an innovative approach. It will analyze differences in healthy years of life, going beyond average indicators (for example healthy life expectancy) to study the entire distributions of years spent in good health; The project activities will include: analysis of international mortality and health prevalence data; application of a mix of statistical and demographic methods; elaboration of the results and preparation of related scientific publications; The following skills are required: knowledge of demographic methods and the basics of probability theory; documented experience with data handling and analysis of large datasets; advanced knowledge of R-language programming; academic English proficiency and ability to draft scientific reports and papers; secs-s/03 - statistica economica
Requirements: Early stage researcher or 0-4 yrs (Post graduate)

Duties: You will be a part of an international team developing open-source tools capable of supporting the development of multi-disciplinary and multi-objective optimized wind farm control functions for grid compliance and services. If you have the skills but not the experience in wind energy science, we would still like to hear from you. The same is valid if you feel you only have part of the skills, but the desire and ability to improve on the rest
Requirements: You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree; Knowledge in one or more of the following fields: Data driven methods ideally with application to wind energy science; Data-driven wind farm layout optimization; Data-driven active power control in large wind power plants; Experience in programming with scientific Python

Duties: Your objective will be to use probabilistic modeling and machine learning to create bioinformatic tools and databases that enable and inspire other researchers to analyze protein isoforms
Requirements: As a formal qualification, you must hold a PhD degree (or equivalent); Strong programming skills; Strong background in probabilistic models or strong math/stats background

Duties: Your objective will be to create the bioinformatic tools that databases that enables isoform-level systems biology
Requirements: You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree; Strong R programming skills; Experience with developing machine learning models, probabilistic modeling or other bioinformatic tools

Duties: Your objective will be to create the bioinformatic tools that enables isoform-level analysis of proteomics data as well as apply them within proteomics
Requirements: You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree; Strong R programming skills; Experience with applied analysis of proteomics or transcriptomics (bulk/single-cell)