Assistant Professor (Lecturer) in Computer Science, Data Science Lancaster University Leipzig Salary: €60,722 to €68,051 Closing Date: Monday 31 July 2023 Interview Date: Wednesday 16 August 2023 Reference: 0721-23 Lancaster University Leipzig, Germany Lancaster University invites applications for one post of Assistant Professor (Lecturer) in Computer Science to join at its exciting new campus in Leipzig, Germany. Located in one of Germany’s most vibrant, livable, and attractive cities, the Leipzig campus offers the same high academic quality and fully rounded student experience as in the UK, with a strong strategic vision of excellence in teaching, research, and engagement. The position is to support the upcoming MSc programme in Data Science, and to complement the department’s current research strengths on Intelligent Systems and Artificial Intelligence. The candidate is expected to have solid research foundations and a strong commitment in teaching Data Science topics such as Data Science Fundamentals, Data Mining, and Intelligent Data Analysis and Visualisation. The ideal candidate should have a completed PhD degree and demonstrated capabilities in teaching, research, and engagement in the areas of Data Science. Candidates should be able to deliver excellent teaching at graduate and undergraduate level, pursue their own independent research, and develop publications in high quality academic journals or conferences. Candidates are expected to have a suitable research track record of targeting high quality journals or a record of equivalent high-quality research outputs. Colleagues joining LU Leipzig’s computer science department will benefit from a very active research team in Leipzig with a focus on Intelligent Systems and Artificial Intelligence in the wider sense, but will also have access to the research environment at the School of Computing and Communications in the UK. We offer a collegial and multidisciplinary environment with enormous potential for collaboration and work on challenging real-world problems especially. German language skills are not a prerequisite for the role, though we are seeking applicants with an interest in making a long-term commitment to Lancaster University in Leipzig. Please note this role is a full time, indefinite-duration appointment based in Leipzig, Germany. The contract is with Lancaster University Leipzig under German law. Ideally we would like the appointed candidate to start at latest on 1st January 2024. The opportunity is unique as the role is permanent after a 6-months probationary period, and offers the opportunity of being promoted to associate professor and professor in line with performance. We also support administrative procedures related to settlement in Germany and assistance in finding accommodation, family integration (school registration for children), German training (for you and your partner), and relocation expenses.

We are a new group at the Chinese Institute for Brain Research (CIBR), Beijing, which focuses on using modern data science and machine learning tools on neuroscience data. We collaborate with various labs within CIBR to develop models and analysis pipelines to accelerate neuroscience research. We are looking for enthusiastic and talented machine learning engineers and data scientists to join this effort. Example projects include (but not limited to) extracting hidden states from population neural activity, automating behavioral classification from videos, and segmenting neurons from confocal images using deep learning.

Interested applying machine learning, applied mathematics & data science tools for analyzing neural connectivity and sequential activation of neural ensembles associated with sensory computations and learning? We are hiring a PhD student ! We offer an excellent and collegial research environment at Kavli Institute for Systems Neuroscience and Norwegian University of Science and Technology (NTNU), in addition to high life-standards of Norway, surrounded by spectacular nature. The deadline for the applications is at end of May 2022. Please spread the word. Apply using this link: https://www.jobbnorge.no/en/available-jobs/job/224137/phd-candidate

The Omics Data Science Lab led by Dr. Jesse Meyer at the Medical College of Wisconsin in Milwaukee seeks postdoctoral fellows or research scientists to spearhead studies in three areas of research focus: 1) Neurodegeneration. We develop iPSC-derived models of neurodegeneration for high throughput multi-omic analysis to discover drugs and enable understanding of neuroprotective pathways. The applicant will have a PhD (or MD with substantial laboratory experience) related to neuroscience or neurobiology. Expertise in Alzheimer’s disease or amyotrophic lateral sclerosis, iPSC-derived neurons, cellular assays, imaging, are desired. 2) Multi-Omics. We develop and apply new mass spectrometry methods to collect quantitative molecular data from biological systems more quickly (Meyer et al., Nature Methods, 2020). The applicant will have a PhD (or MD with substantial laboratory experience) related to analytical chemistry, especially mass spectrometry-based proteomics and/or metabolomics and/or associated bioinformatic skills especially machine learning. The multi-omic analysis methods we develop will be paired with machine learning to understand changes in metabolism associated with disease. 3) Data Science. We develop and apply machine learning methods to biological problems (Meyer et al. JCIM 2019, Overmyer et al. Cell Systems 2021, Dickinson and Meyer bioRxiv 2021). The applicant will have a PhD (or MD with substantial laboratory experience) related to computational biology especially machine learning and deep learning. Expertise in cheminformatics is preferred. Projects relate to chemical effect prediction and automated interpretation of omic data. Applicants must have experience in one of the above focus areas, and interest in learning the other focus areas is desired. The Omics Data Science Lab led by Dr. Jesse Meyer is a basic and translational research group in the Department of Biochemistry at the Medical College of Wisconsin. We have our own mass spectrometer (Orbitrap Exploris 240 with FAIMS) and related support equipment, and access to abundant human samples paired with EHR data through the MCW tissue bank and clinical data warehouse. The Medical College of Wisconsin is the 3rd largest private medical school in the United States and ranks in the top 1/3 of medical schools for NIH funding received. Successful applicants are expected to work independently in a collegial and supportive yet demanding environment. Potential for self-funding is welcome but not essential. Inquiries and applications (including CV, contact info for 2-3 references, and reprints of 2 most significant publications) should be directed to: Jesse G. Meyer, Ph.D. Assistant Professor, Department of Biochemistry, Medical College of Wisconsin jesmeyer@mcw.edu www.jessemeyerlab.com

The Department of Engineering Mathematics at the University of Bristol is seeking an outstanding candidate to fill the role of Professor in Artificial Intelligence. You will have the opportunity to provide visionary leadership to the department and its staff, students, & partners, helping to strengthen and further develop our already impressive research and teaching programs in AI. Our Intelligent Systems Group supports the Faculty of Engineering's AI/Data Science Theme, fostering an inclusive environment for all.

Two new Assistant Professor positions available at Lancaster University Leipzig, one with a focus on data science, one focussed on cyber security. Lancaster University Leipzig is a young branch campus of Lancaster University, based in Leipzig Germany. The department is focussed on intelligent systems, including topics such as emergent behaviour, unconventional computing, quantum software engineering, and robotics. These are grade 8 openings, so we would expect to see a research plan and teaching experience from interested applicants (grade 7 is the typical entry-level asst. prof. level).

The job is a W3 Full Professorship for Artificial Intelligence in interactive Systems at Technische Universität Braunschweig. The role involves expanding the research area of data-driven methods for interactive and intelligent systems at the TU Braunschweig and strengthening the focal points 'Data Science' and 'Reliability' of the Department of Computer Science. The position holder is expected to have a strong background in Computer Science with a focus on Artificial Intelligence/​Machine Learning, specifically in the areas of Dependable AI and Explainable AI. The role also involves teaching, topic-related courses in the areas of Artificial Intelligence and Machine Learning to complement the Bachelor's and Master's degree programs of the Department of Computer Science.

Kairos Research is seeking a full-time Cognitive Data Scientist to help execute and grow our expanding portfolio of government-sponsored research in the human sciences. The Cognitive Data Scientist will play a major role in supporting our human performance data modeling and data analytics efforts with the Air Force Research Laboratory, as well as other projects that involve extracting insights from a wide variety of physiological and cognitive datasets (ranging from wearable sensors data to cognitive and behavioral performance data). The ideal candidate is a highly creative, self-motivated individual who possesses a deep understanding of leading-edge techniques in data science, statistical modeling, and/or machine learning. The candidate should also possess a strong publication record and a willingness and ability to seek independent research funding. Additionally, because Kairos is a small company with a highly collaborative work culture, we especially seek candidates who are outgoing and enjoy interacting with their colleagues and with our government sponsors.

Candidate is expected to conduct active research and education in the field of Emergent AI studies. This involves using data science and AI technology to generate scientific principles through co-creative investigation on principles, problem solving, and design underlying social, organizational, human, natural phenomena, and art, and through the exploring methodologies for such principles.

The Initiative for Data & Artificial Intelligence at Universidad de Chile is looking for Postdoctoral Researchers to join a collaborative team of PIs working on theoretical and applied aspects of Data Science. The role of the postholder(s) is twofold: first, they will engage and collaborate in current projects at the Initiative related to statistical machine learning, natural language processing and deep learning, with applications to time series analysis, health informatics, and astroinformatics. Second, they are expected to bring novel research lines affine to those currently featured at the Initiative, possibly in the form of theoretical work or applications to real-world problems of general interest. These positions are offered on a fixed term basis for up to one year with a possibility for a further year extension.

The Cyprus Institute invites applications for a highly qualified and motivated individual to join the Institute as a Postdoctoral Research Fellow in Machine Learning and Data Science for Climate Science in CaSToRC. The successful candidate will apply Machine Learning for investigating key processes of the Earth System, including (but not limited to) the following: Extreme event (weather, temperature, precipitation, etc.) risk detection, Data-driven and hybrid modeling of the Earth system, Using machine learning to develop new parameterizations for climate models, Causal inference in the context of climate change, Machine learning in support to air quality modelling for exposure mapping, super-resolution, short-term forecasts and long-term projections. The candidate will be working primarily with Prof. Constantine Dovrolis, Prof. Theo Christoudias and Prof. Johannes Lelieveld. The appointment is for a period of 2 years, with the possibility of renewal subject to performance and the availability of funds.

We have two fully funded PhD scholarships in data science, with an emphasis on neural network applications/research, available at our Institute for Analytics and Data Science.

The Department of Computer Science at University of Miami is inviting applications for tenure-track or tenure eligible faculty positions at levels of Associate Professor and Professor. The successful candidates must conduct research in Data Science, including areas such as Machine Learning, Deep Learning, Computer Vision, Cognitive Cybersecurity, Blockchain, Real-time Analytics, Streaming Analytics, Cyber-analytics, and Edge Computing, and are expected to develop/maintain an internationally recognized research program. The selected candidate will be expected to teach classes at the undergraduate and graduate levels. The faculty in these positions will be housed primarily in the Department of Computer Science and will have responsibilities in the Institute for Data Science and Computing (IDSC).

The KINDI Center for Computing Research at the College of Engineering in Qatar University is seeking high-caliber candidates for a research faculty position at the level of assistant professor in the area of artificial intelligence (AI). The applicant should possess a Ph.D. degree in Computer Science or Computer Engineering or related fields from an internationally recognized university and should demonstrate an outstanding research record in AI and related subareas (e.g., machine/deep learning (ML/DL), computer vision, robotics, natural language processing, etc.) and fields (e.g., data science, big data analytics, etc.). Candidates with good hands-on experience are preferred. The position is available immediately.

The Faculty of Engineering, Computer Science and Psychology, Institute of Neural Information Processing, is seeking to fill the position of Professor (W3) of Machine Learning. The research focus of this professorship should center around fundamental methodological contributions to machine learning. This includes expertise in statistical learning methods, neural network architectures, cognitive modeling of learning and adaptation processes, relational and structured learning models, and related topics. The ideal candidate will demonstrate connections to the faculty's key focus area, 'Cognitive Systems', and the strategic development area 'Data Science'. Moreover, affiliations to fields such as medical image processing, psychology of cognitive processes, technical adaptive systems, and relevant topics in other faculties of the university are desirable. Collaborative involvement with companies in the Science Park of Ulm and the newly founded DLR Institute for Secure AI is also welcome. Experience in acquiring third-party funding and participation in national and international research collaborations are required attributes. In teaching, the professorship will cover the area of 'Machine Learning' and practical and applied computer science topics in the core curriculum of the bachelor's degree programs in computer science. Teaching of advanced modules is, in particular, expected in the master's degree program 'Artificial Intelligence' and in the international master's degree program 'Cognitive Systems'. Modules at the master’s level are primarily taught in English. The candidate's excellence in teaching will be evident through appropriate teaching evaluations. Participation in academic administration is expected. The professorship is linked to the role of deputy director for the Institute of Neural Information Processing.

The Department of Psychology in the College of Arts and Sciences at American University invites applications for a full-time, tenure-track position at the rank of Assistant or Associate Professor beginning August 1, 2024. Rank will be dependent on experience and stature in the field. Depending on qualifications, the appointee to this position may be recommended for tenure at the time of hiring. In addition to scholarship and teaching, responsibilities will include participation in department, school and university activities. We welcome applications from candidates engaged in high-quality research in Cognitive or Social Psychology. The University has areas of strategic focus for research in Data Science and Analytics, Health, Security, Social Equity, and Sustainability. Priority will be given to outstanding researchers who can contribute meaningfully to one or more of these areas.

The Department of Computer Science in the College of Arts and Sciences at American University invites applications for a full-time, open-rank, tenure-line position beginning August 1, 2024. Applicants should have a PhD or an anticipated PhD completion by August 2024 in Computer Science or related fields. Depending on experience and qualification, the appointee to this position may be recommended for tenure at the time of hiring. Candidates can apply at the assistant, associate, or full professor level and we welcome applications from both academic and nonacademic organizations. We are looking for candidates who are excited at the prospect of joining a growing department where they will be able to make their mark. Preference will be given to candidates with a record of high-quality scholarship. For candidates applying at the associate or full professor level, a record of external funding is also expected. The committee will consider candidates engaged in high-quality research in any area of Computer Science related to Artificial Intelligence (E.g., Natural Language Processing, Machine Learning, Network Analysis, Information Visualization), Theoretical Computer Science (Computational Theory, Graph Theory, Algorithms), Cybersecurity, and other traditional areas of Computer Science (E.g., Software Engineering, Database Systems, Graphics, etc.). The University has areas of strategic focus for research in Data Science and Analytics, Health, Security, Social Equity, and Sustainability. Applicants from historically underrepresented minority and identity groups are strongly encouraged to apply. In addition to scholarship and teaching, responsibilities will include participation in department, school, and university service activities. Attention to Diversity, Equity and Inclusion (DEI) in all activities within the academic environment are expected.

The Department of Psychology at the University of Miami invites applications for two full-time, tenure-eligible, or tenure-track faculty members to join our department in August 2024. One position is in the department’s Adult Division, and the other is the Cognitive & Behavioral Neuroscience division. The specific area for both positions is open. For the Adult Division, areas of focus could include basic research on affect, cognitive science, and/or mechanistic studies related to mental health or the impact of disparities. Scholars with expertise in lab-based experimental, neurophysiological, computational, and/or mobile health/digital phenotyping methods are welcome. Individuals with interests in data science, including advanced quantitative techniques, big data, and machine learning are also encouraged to apply. For the Cognitive & Behavioral Neuroscience Division, we are particularly interested in individuals who incorporate innovative and sophisticated cognitive, affective, or social neuroscience methods into their research program.

The Max Planck Institute for Intelligent Systems and the Universities of Stuttgart and Tübingen collaborate to offer an interdisciplinary Ph.D. program, the International Max Planck Research School for Intelligent Systems (IMPRS-IS). This doctoral program will accept its eighth generation of Ph.D. students in spring of 2024. This school is a key element of Baden-Württemberg’s Cyber Valley initiative to accelerate basic research and commercial development in artificial intelligence and robotics. We seek students who want to earn a doctorate while contributing to world-leading research in areas such as: Biomedical Technology, Computational Cognitive Science, Computer Vision and Graphics, Control Systems and Optimization, Data Science, Haptics and Human-Computer Interaction, Machine Learning, Micro- and Nano-Robotics, Neuroscience, Perceptual Inference, Robotics and Human-Robot Interaction, Soft Robotics and Materials.

The Department of Computer Science in the College of Arts and Sciences at American University invites applications for a full-time, open-rank, tenure-line position beginning August 1, 2024. Applicants should have a PhD or an anticipated PhD completion by August 2024 in Computer Science or related fields. Depending on experience and qualification, the appointee to this position may be recommended for tenure at the time of hiring. Candidates can apply at the assistant, associate, or full professor level and we welcome applications from both academic and nonacademic organizations. We are looking for candidates who are excited at the prospect of joining a growing department where they will be able to make their mark. Preference will be given to candidates with a record of high-quality scholarship. For candidates applying at the associate or full professor level, a record of external funding is also expected. The committee will consider candidates engaged in high-quality research in any area of Computer Science related to Artificial Intelligence (E.g., Natural Language Processing, Machine Learning, Network Analysis, Information Visualization), Theoretical Computer Science (Computational Theory, Graph Theory, Algorithms), Cybersecurity, and other traditional areas of Computer Science (E.g., Software Engineering, Database Systems, Graphics, etc.). The University has areas of strategic focus for research in Data Science and Analytics, Health, Security, Social Equity, and Sustainability. Applicants from historically underrepresented minority and identity groups are strongly encouraged to apply. In addition to scholarship and teaching, responsibilities will include participation in department, school, and university service activities. Attention to Diversity, Equity and Inclusion (DEI) in all activities within the academic environment are expected.

Changes in ocular hemodynamics may be indicative of pathological conditions in the eye (e.g. glaucoma, age-related macular degeneration), but also elsewhere in the body (e.g. systemic hypertension, diabetes, neurodegenerative disorders). Thanks to its transparent fluids and structures that allow the light to go through, the eye offers a unique window on the circulation from large to small vessels, and from arteries to veins. Deciphering the causes that lead to changes in ocular hemodynamics in a specific individual could help prevent vision loss as well as aid in the diagnosis and management of diseases beyond the eye. In this talk, we will discuss how mathematical and computational modelling can help in this regard. We will focus on two main factors, namely blood pressure (BP), which drives the blood flow through the vessels, and intraocular pressure (IOP), which compresses the vessels and may impede the flow. Mechanism-driven models translates fundamental principles of physics and physiology into computable equations that allow for identification of cause-to-effect relationships among interplaying factors (e.g. BP, IOP, blood flow). While invaluable for causality, mechanism-driven models are often based on simplifying assumptions to make them tractable for analysis and simulation; however, this often brings into question their relevance beyond theoretical explorations. Data-driven models offer a natural remedy to address these short-comings. Data-driven methods may be supervised (based on labelled training data) or unsupervised (clustering and other data analytics) and they include models based on statistics, machine learning, deep learning and neural networks. Data-driven models naturally thrive on large datasets, making them scalable to a plethora of applications. While invaluable for scalability, data-driven models are often perceived as black- boxes, as their outcomes are difficult to explain in terms of fundamental principles of physics and physiology and this limits the delivery of actionable insights. The combination of mechanism-driven and data-driven models allows us to harness the advantages of both, as mechanism-driven models excel at interpretability but suffer from a lack of scalability, while data-driven models are excellent at scale but suffer in terms of generalizability and insights for hypothesis generation. This combined, integrative approach represents the pillar of the interdisciplinary approach to data science that will be discussed in this talk, with application to ocular hemodynamics and specific examples in glaucoma research.

The presentation will provide an overview of the expanding role of genetic factors in epilepsy. It will delve into the fundamentals of this field and elucidate how digital tools and resources can aid in the re-evaluation of genetic test results. In the initial segment of the presentation, Dr. Lal will examine the advancements made over the past two decades regarding the genetic architecture of various epilepsy types. Additionally, he will present research studies in which he has actively participated, offering concrete examples. Subsequently, during the second part of the talk, Dr. Lal will share the ongoing research projects that focus on epilepsy genetics, bioinformatics, and health record data science.

What does an executive at a South African Bank, a machine learning lead, and a CEO of an AI company have in common? They all will be on a panel talking about careers in Data Science, Machine Learning and Artificial Intelligence

Tutorial on Notebook workflows for reproducible data science.

We will highlight recent technological and methodological advances in deploying miniaturized technologies that can monitor the spatial electrophysiologic patterns of the visceral nervous system. As an example, we will discuss recent developments of thin, stretchable, wireless biosensor patches that can be embedded within routinely used medical adhesives for recording electrophysiologic patterns of the GI tract. We will also showcase recent developments in array signal processing that enable non-invasive tracking, and source localization, of the slow wave patterns associated with the GI tract. We will illustrate how such systems can also be used in tandem with novel miniaturized pacing devices to can enable closed-loop neuromodulation of the enteric nervous system. We will conclude with a summary of the knowns and unknowns in how multi-organ physiology research, technology miniaturization, and data science may create unique opportunities for the intersection of electrical engineering and neuroscience.

In urban environments, social boundaries are the areas that emerge from processes of economic inequality and social segregation. These boundaries are important, as they serve both as areas of interaction and conflict. By applying geographical thinking to classic methods in data science, we can better understand where these boundaries emerge and how they delineate communities. In this talk, I’ll explain a bit about the basics of “boundary detection” in urban analytics. I’ll present a new method, the “geosilhouette,” that builds on previous methods of identifying the boundaries between clusters. And, finally, I’ll show how this can change our understanding of urban community.

The presentation will present the work of the Space Enabled Research Group at the MIT Media Lab. The mission of the Space Enabled Research Group is to advance justice in Earth’s complex systems using designs enabled by space. Our message is that six types of space technology are supporting societal needs, as defined by the United Nations Sustainable Development Goals. These six technologies include satellite earth observation, satellite communication, satellite positioning, microgravity research, technology transfer, and the infrastructure related to space research and education. While much good work has been done, barriers remain that limit the application of space technology as a tool for sustainable development. The Space Enabled Research Group works to increase the opportunities to apply space technology in support of the Sustainable Development Goals and to support space sustainability. Our research applies six methods, including design thinking, art, social science, complex systems, satellite engineering and data science. We pursue our work by collaborating with development leaders who represent multilateral organizations, national and local governments, non-profits and entrepreneurial firms to identify opportunities to apply space technology in their work. We strive to enable a more just future in which every community can easily and affordably apply space technology. The work toward our mission covers three themes: 1) Research to apply existing space technology to support the United Nations Sustainable Development Goals; 2) Research to design space systems that are accessible and sustainable; and 3) Research to study the relationship between technology design and justice. The presentation will give examples of research projects within each of these themes.