Duration: 3+1 y
Duties: Im Rahmen eines Forschungsprojektes mit dem Deutsch; Französischem Forschungsinstitut Saint; Louis (ISL) ist voraussichtlich ab 1.10.2024 eine Promotionsstelle für die Dauer von 3 Jahren zu besetzen, eine Verlängerung auf 4 Jahre ist möglich. Im Rahmen dieses Projektes sollen neue numerische Raum; Zeit Diskretisierungsverfahren (FEM/BEM) zur Lösung inverser Probleme der Wellengleichung entwickelt und implementiert werden, ein Vergleich mit experimentellen Daten ist vorgesehen
Requirements: Hervorragender Abschluss eines Universitätsstudiums in Mathematik, Physik, oder Ingenieurwissenschaften. Gewünschte Qualifikationen: Kenntnisse in der Numerik partieller Differentialgleichungen, Programmierkenntnisse

Duties: Model optimization: collaborate with data scientists to improve existing machine learning model training and evaluation pipelines, optimize the model training pipeline speed for faster iteration; Model Deployment: optimize the model inferencing performance through quantization and model conversion, define and leverage appropriate resources for model hosting and inferencing; Inference Pipeline product prioritization: work with data scientists and data engineers to design and implement the data pipelines for machine learning models that will support the current and future needs of our business; Service Deployment: build continuous integration, testing, and scalable deployment pipelines in cloud computing environments for machine learning services
Requirements: BS or above in Computer Science, Software Engineering, Data Science, or a related field; 2 years of industry experience building ML infrastructure at scale; 1 year of experience in developing and deploying large-scale systems, version control, scaling and monitoring; Experience in Machine Learning frameworks (scikit-learn, Tensorflow, Pytorch), big data frameworks (Spark/Hadoop/Flink), and experience in resource management and task scheduling for large-scale distributed systems; Proficient in Python/SQL and of C++/Go, with deep knowledge of Linux and CD tools (e.g. Git)

Duties: As a Deep Learning Engineer, you will be helping to build the ML/DL framework that drives our core business. You are not only implementing new models on top of our existing framework to solve new customer problems, but you are helping to improve the core framework that unifies all the problems we are solving. In particular, the differentiation of our frameworks and models are that they are computationally and numerically much more efficient (orders of magnitude) than state of the art techniques
Requirements: MS or PhD preferred; 3+ years of industrial work experience; Strong C++ programming experience; Expertise in Machine Learning, Deep Learning, Computer Vision, NLP, AI or related field which is heavily computational math-based; Experience developing large scale deployable software products; Experience working in large, complex codebases; Familiarity with version control tools such as GIT, CVS, SVN, etc; Familiarity with project management tools such as BitBucket, Jira, etc; BS in Computer Science/Engineering or related software-based field

Duties: Develop and extend machine learning methods for big cancer Omics data such as single-cell omics data and spatial transcriptomics data; Develop bioinformatics pipelines for analyzing high dimensional immunological data; Develop novel visualization tools for interpreting big cancer Omics data; Discover new predictive biomarkers for cancer prognosis; Collaborate on a variety of cancer and bioinformatics research projects
Requirements: PhD in Bioinformatics, Statistics/Biostatistics, Applied Mathematics, Data Science, Computer Science, or related fields. Research background/experiences in Bioinformatics, Statistics, Computational Biology, Machine Learning, or Computer Science. A highly motivated and independent researcher with a strong quantitative scientific background. Programming experience in statistical program R and/or scripting languages such as Perl/Python on Unix/Linux systems

Duties: Participate in implementation and evaluation of leading-edge machine learning methods related to cancer immunotherapy; Explore large-scale immunological datasets, including genomic, transcriptomic, mass spectrometry, and structural data, to derive and integrate orthogonal contributors of effective immunotherapy design; Stay abreast of scientific findings and technological developments and continuously improve computational methodology; Maintain detailed documentation of data analysis methods and results; Present findings and participate in cross-function team meetings
Requirements: MS degree in Computational Biology, Bioinformatics, Computer Science, or a related field; Strong track record in machine learning algorithm development, preferably with applications in immunology, genomics, or personalized medicine; Proficiency in handling and interpreting large-scale biological datasets, including genomic and proteomic data; Strong programming skills in Python/R and with ML frameworks (e.g. PyTorch)

Duties: As a Deep Learning Scientist, you will design high-performance, state-of-the-art, hybrid architectures for image-based classification, segmentation, labeling, and object detection. This position requires strong theoretical foundations, excellent engineering skills, and sound scientific method. Candidates must have broad and deep proficiency in the foundations of machine learning, CNNs, image processing and computer vision. Candidates must also be adventurous and enthusiastic about an early startup experience!
Requirements: Strong academic foundations from a competitive university/laboratory (Ph.D. preferred); Fluent with state-of-the-art techniques for image-based machine learning; Substantial experience architecting, training, optimizing and evaluating image-based ConvNets; Practical experience building pixel-based image segmentation/boundary/classification networks; Strong applied math skills in linear algebra and linear & non-linear optimization; Solid scientific method & excellent data analysis skills

Duties: Design and build scalable infrastructure that enables training, evaluating and deploying machine learning models over billions of collected historical data points; Design and develop tools for monitoring the performance of machine learning models at scale; Design and develop lineage and artifact tracking infrastructure for training data, ML models and experiments; Design and develop reproducible ML Pipelines that help interpretability and trustworthiness of ML models; Embrace and champion engineering best practices within your group and beyond; Produce clean, high-quality code, tests, and written documentation
Requirements: 5+ years of non-internship professional software development experience; 5+ years of programming with at least one software programming language experience; 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience; Experience as a mentor, tech lead or leading an engineering team; Experience in machine learning, data mining, information retrieval, statistics or natural language processing

Duties: Design, develop, and implement software programming for both internal and external products, exceeding customer expectations with a focus on quality and on-time delivery; Ensure the overall functional quality of released products across all platforms and mechanisms; Lead major projects within the product area, providing technical guidance and promoting innovation; Consult with customers on future upgrades and products, influencing technical direction; Provide high-level technical expertise, including in-depth software systems programming and analysis; Mentor junior engineers, demonstrating independence and technical expertise
Requirements: Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related field; +8 years of experience in software development, with a specialization in data analysis and machine learning; Proficiency in programming languages such as Python, Java, or C++; Experience with machine learning frameworks (e.g., TensorFlow, PyTorch)

Duties: Use machine learning and analytical techniques to create scalable solutions for business problems; Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes; Design, develop, evaluate and deploy, innovative and highly scalable ML models; Work closely with software engineering teams to drive real-time model implementations; Work closely with business partners to identify problems and propose machine learning solutions; Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance; Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production; Leading projects and mentoring other scientists, engineers in the use of ML techniques
Requirements: 5+ years of building models for business application experience; PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience; Experience in patents or publications at top-tier peer-reviewed conferences or journals; Experience programming in Java, C++, Python or related language; Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Duties: Participate in the construction of a multi-party joint modeling and data analysis platform; Work with product teams to understand key privacy requirements from TikTok product family and convert research outcomes into technical solutions and product prototypes; Work with research teams for complex experiments requiring optimized algorithms running on large datasets or sophisticated data processing; Build open-source tools and infrastructure for privacy related research and engage with community contributors in external events including meetups, hackathons, summits
Requirements: PhD or Master's degree in Computer Science or a related field; Familiar with federated learning/distributed machine learning algorithms and experienced in federated learning frameworks and applications development; Familiar with machine learning and deep learning frameworks, like TensorFlow, Pytorch, JAX; Proficiency in at least one of the following programming languages, Go, C++, Python, Rust, Java; Ability to work globally and collaboratively within a team

Duties: Computational analysis of large, complex, single cell genomics datasets from in vitro cellular model systems ; Deliver testable hypotheses/insights from complex high-dimensional data to inform target selection ; Linking results and insights between internal and public data, as well as orthogonal data such as human genetics. ; Identify and validate approaches to improve quality and efficiency of hypothesis generation from model systems ; Maintain awareness of emerging methods in computational biology and applications for novel omics technologies ; Provide ad-hoc bioinformatics support to cross-disciplinary project teams 
Requirements: PhD in Bioinformatics, Biostatistics, Computer Science, Computational Biology, Genetics, Mathematics, Physics, Statistics or other related discipline ; 2-3 years post PhD experience applying quantitative approaches to solve biological problems ; Knowledge and experience of single-cell transcriptomic data and analyses; additional modalities such as histone modification data analysis considered a plus. ; Strong knowledge of applied statistics and machine learning (in particular deep generative models) ; Strong statistical and scripting programming skills (Python/R/etc.) 

Duties: You lead several internal development teams and are responsible for external software development partners; You lead strategically important projects; You manage the software development lifecycle of our digital products and support the product units with their digital requirements; Together with various users and stakeholders from product units, you analyze the requirements regarding research & development of software solutions; You are innovative in the development of product features and capabilities along our agile processes; You actively participate in the continuous improvement of processes and procedures
Requirements: Higher education (university) in a technical field (computer science, engineering) or equivalent professional experience; Several years of professional experience in managing software development projects and software teams, ideally in an international environment; You are familiar with traditional and agile development methods and have the relevant experience; You are proficient in the use of modern software modeling tools and are familiar with current software architecture and design principles; You are characterized by strong analytical skills and enjoy interacting with various stakeholders; You have very good communication skills (written and spoken) in German and English and feel comfortable in an international environment

Department: Information Science
Duration: 1 y
Duties: This research program intends to contribute to recognizing local varieties of fruit trees through the analysis of digital images. In this research program, artificial intelligence and machine learning methods will be developed and implemented based on datasets of leaves and fruits images, which, through elements such as shape and color, provide information on cultivar name, the state of health and phenological development of the plants in question. The developed algorithms will address problems of classification, segmentation, compression and comparison
Requirements: Early stage researcher or 0-4 yrs (Post graduate)

Duties: The postholder will develop numerical models using finite-difference methods with increasing complexity and benchmark against analytical solutions, adapt the existing theoretical and computational frameworks, including rheological and thermochemical models, relevant for modelling magmatic-tectonic cycles at mid-ocean ridge. You will also write manuscripts, present at national and international conferences and workshops and collaborate with colleagues in research groups and partner institutions
Requirements: You will hold, (at the time of starting the post), a PhD/DPhil in a relevant field (e.g. geodynamics, theoretical and/or applied physics, engineering or applied mathematics) together with experience relevant to the objectives of the projects. You will also have experience with computational modelling of continuum mechanical phenomena based on the solution of partial differential equations. You must have the ability to manage your own academic research and associated activities and excellent communication skills including the ability to write for publication, present research proposals and results, and represent the research group at external meetings

Duties: Develop theoretical and computational models for interfacial flow and wetting on cell membranes; Implement and solve numerically the theoretical membrane model; Collaborate with experimentalists; Develop independence and be self-driven to advance with their research project; Work in an interdisciplinary team with expertise in mechanics, biology, physics and biophysics; Follow our PhD program that include an educational component
Requirements: Master’s degree or equivalent in mechanics, fluid mechanics, biophysics, physics or applied mathematics; Excellent oral and written communication skills in English

Department: Mathematics; Applied Mathematics
Duration: 1 y
Duties: Numerical methods for environmental monitoring models based on differential and integral equations
Requirements: Early stage researcher or 0-4 yrs (Post graduate)

Workload: 80-100%
Duties: Gestaltung, prototypische Umsetzung und Validierung von XR-Anwendungen (Unity) mit Konversationsagenten (LLM); Projektmitarbeit als Developer (Problemanalysen, Lösungsgestaltung, Implementierung); Unterrichtstätigkeit; Weiterverwendung und -entwicklung von Forschungs- und Projektergebnissen (Frameworks, Code-Basen, Lehrmaterialien, Folgeprojekte, Publikationen); Qualifizierung durch zusätzliche Aufgaben wie z.B. Product Ownership, Projektmanagement, Fördermittelanträge und Publikationen
Requirements: Für diese vielseitige Tätigkeit setzen wir eine Informatikausbildung oder entwicklungsorientierte Ausbildung im Bereich Interaktions- oder Gamedesign (Bachelor oder Master) voraus. Sie bringen Erfahrung mit aktuellen Methoden (u.a. Agile, UCD), Werkzeugen (DevOps) und Technologien (XR für Head Mounted Displays: Unity/C# oder NLP: z.B. SpaCy oder NLTK, 3D-Modellierung: z.B. Blender) mit

Duties: Simulation, and prototyping of models for the design of antennas for micro and millimeter-wave applications; Analyzing, designing, and prototyping phased array antennas for micro and millimeter-wave applications; Applying different additive manufacturing techniques for antenna prototyping; Measurement of antenna parameters; Disseminating results through scientific publications and conferences; The candidate is expected to actively contribute to the different research projects at SnT, either coordinating technical contributions and/or preparing project deliverables; Preparing new research proposals to attract industrial, national, and European projects; Providing assistance for Ph.D. students
Requirements: Master (or equivalent) in Telecommunication Engineering or Electrical Engineering focused on antenna design and their implementation using additive manufacturing techniques. The topic of antennas and metasurface design for satellite systems is desired but not mandatory; Sound publication track record in relevant international conferences and top journals in the following research areas; Experience with machine learning and artificial intelligence is highly desirable; Strong design skills in CST Microwave Studio, Advance Design System (ADS), and High-Frequency Simulations Software (HFSS) design tools are mandatory; Experience in MEEP programming is desirable but not mandatory; Strong programming skills in MATLAB. Python, JULIA, and C++ are desirable but not mandatory

Duties: The objective of this project is to develop automated means to continuously monitor the performance of AI models (including NLP models) developed by BGL BNP Paribas and to determine when and how to retrain these models in order to improve their performance. Achieving these objectives requires addressing crucial research challenges such as the definition of proper quality metrics across the bank’s use cases, the identification and explaination of the limitations and blanks spots of the models, and the design of sustainable improvement mechanisms. Overall, the project supports BGL BNP Paribas in scaling-up their AI and data science activities through ground-breaking research, thereby enabling the widespread dissemination of AI products and services throughout the bank. The project is held in close collaboration with BGL-BNP Paribas and, as the successful candidate, you will be expected to program prototype tools showcasing the practical benefits of your research outcomes
Requirements: The candidate should possess an PhD degree (or equivalent) in computer science with strong skills in software engineering, programming, and artificial intelligence, as well as good knowledge of computer science in general. The ideal candidate should have some knowledge and/or experience in most of the following topics: Programming (Python is a must, Java is an asset) Data science, data engineering, data collection and storage Artificial intelligence, machine learning Natural Language Processing is a plus (but not mandatory)

Duties: We seek a highly motivated bioinformatician or biostatistician who is well versed in the statistical and machine learning analysis of biomedical data and bioscientific programming for a project on the study of neurodegenerative diseases. The candidate should have experience in the analysis of large-scale biomedical data (omics, clinical, imaging, or other large biological datasets), using statistical methods, pathway/network analysis or machine learning/artificial intelligence. The candidate will conduct integrative analyses of biomedical datasets, focusing on omics and clinical data to predict clinical outcomes of interest (e.g., disease progression scores). This will include implementing and applying software analysis pipelines and interpreting disease-related data together with experimental and clinical collaborators. Classification models guided by prior mechanistic knowledge will be built, exploiting the known grouping structures among features in the omics data, using dedicated s...
Requirements: The candidate will have an MSc or equivalent degree in bioinformatics, biostatistics, machine learning, computational biology, or related subject areas; Prior experience in large-scale data processing and statistics/machine learning is required; Previous work and publications in bioinformatics or biostatistics analysis of large-scale biomedical data (e.g., omics, clinical, imaging, other biomedical data) should be outlined in the CV; Demonstrated skills and knowledge in omics data analysis, machine learning, pathway and network analysis are highly advantageous; The candidate should have a cross-disciplinary aptitude, strong organizational and interpersonal skills, and a keen interest in collaborative biomedical research; Fluency in oral and written English

Workload: 80-100%
Duties: Betrieb und Weiterentwicklung von PowerShell-basierten Workflows, Automatismen und Systemschnittstellen sowie des zentralen IT Service Portals und Personendatenverwaltungssystems basierend auf dem Microsoft System Center Service Manager (SCSM) und Operaio ITSP Web Frontend; Mitarbeit in Projekten durch Konzeption und Implementation neuer Lösungen zur Optimierung des Automatisierungsgrades; Administration von Cloud Services (Microsoft Azure, etc.) und Pflege systemübergreifender automatisierter Schnittstellen
Requirements: Informatikausbildung auf Niveau EFZ Informatik/Technische Ausbildung mit entsprechender Weiterbildung; Gute PowerShell Kenntnisse; Kenntnisse in XML, HTML/XHTML von Vorteil; Erfahrung mit den Microsoft Systemcenter Produktpalette (SCSM, SCORCH, MECM/SCCM) sowie Windows Systemadministration; Erfahrung mit dem ITIL V3/V4 Framework sind wünschenswert; Sehr gute Deutsch und Englisch Kenntnisse in Wort und Schrift; Französisch Kenntnisse sind von Vorteil

Duties: Attività di ricerca applicata nel campo delle applicazioni di salute di precisione abilitate dall'IA, utilizzando vari algoritmi per consentire il riutilizzo dei dati sanitari esistenti e di altri dati sanitari a supporto della ricerca clinica e dell'assistenza clinica; Applicazioni di IA responsabile di algoritmi di apprendimento automatico superficiale e profondo in ambito sanitario; Scrivere articoli scientifici per riviste e atti di conferenze, documenti di progetto e relazioni interne; Presentare i risultati della ricerca a un vasto pubblico, tra cui conferenze, workshop e riunioni di revisione dei progetti; Partecipare all'insegnamento e al tutoraggio degli studenti
Requirements: Laurea magistrale in informatica, scienza dei dati, informatica medica, ingegneria del software o campi correlati, già conseguita o in fase di completamento; Esperienza nell'apprendimento automatico superficiale e profondo; Forte motivazione e impegno nella ricerca e nella pubblicazione in conferenze e riviste di alto livello; Forti capacità di programmazione, con familiarità con Python (o Java); Conoscenza dell'inglese scritto e parlato; Buone capacità organizzative, capacità di lavorare in modo indipendente e proattivo

Duties: The research program in the lab focuses on developing computational methodologies and designing integrative data science approaches to study chromatin epigenomics and gene regulation. Current ongoing projects include: multi-omics integration-based algorithm development for transcriptional regulation prediction; model-based algorithm development for single-cell epigenomics and spatial multi-omics data analysis; statistical and computational modeling of phase-separated transcriptional condensation; global epigenetic and transcriptional regulation in T-cell immunity and various human cancer systems, etc
Requirements: A Ph.D. or equivalent degree in any quantitative science, including but not limited to Bioinformatics, Computational Biology, Applied Mathematics, Statistics, Physics, Chemistry, Computer Science; Proficient in Python (or C/C++) & R programming; Strong quantitative background (e.g., statistical modeling, machine learning, computational or theoretical physics, etc.) or computational genomics experience (e.g., high-throughput sequencing data analysis, etc.)

Duties: As a Senior ML/NLP Engineer, you will collaborate with a team of 3-4 brilliant and curious people. You will play a key part in enhancing our Natural Language Processing technology ecosystem and get to partner with product, engineering and design to bring new product features to life. You, along with your team, will get to put your stamp on an evolving ML roadmap that will increase value for our Enterprise level customers and their internal users
Requirements: BA/BS in a field emphasizing mathematics and/or science research. MA/MS/PhD preferred; 6+ years of experience using machine learning software and relevant programming languages, such as Python, PyTorch, Pandas and Numpy; 6+ years of relevant work experience in natural language processing and machine learning, with 2+ years of experience with training and deploying large language models; 6+ years of relevant work experience with databases, such as SQL and NoSQL

Duties: Work directly with the business to understand their business processes and aims, then identify how analytical solutions could help deliver value for them. This would include being accountable for: Executing specific use cases generated by your manager; Identifying data elements needed and where to get them (including proxies); Assembling data sets independently using knowledge of Highmark operational and analytic data structures; Deliver the analytical solution to a specific business problem
Requirements: Master's Degree in Analytics, Mathematics, Physics, Computer and Information Science, Engineering or closely related field