Join this multidisciplinary project and collaborate with a dynamic team of researchers to advance the science and practice of groundwater sustainability, and the role of nature-based infrastructure in reducing the impacts of climate change. Project Overview: This is an EPA-funded and collaborative project between the Department of Bioengineering, Civil Engineering, and Environmental Engineering at Florida Gulf Coast University, and the Department of Earth, Ocean, and Atmospheric Science at Florida State University. The project focuses on addressing the challenges of sea-level rise, changing precipitation patterns, and rapid socioeconomic development, which pose threats to groundwater and community resilience in South Florida. The project will assess the efficacy of nature-based solutions in enhancing groundwater recharge and maintaining ecosystem functions through an integrated modeling approach combining surface-water groundwater (SW-GW) models and human activities.

Job Description

Typical duties include but not limited to:

• Use an existing regional density-dependent SW-GW model to assess the impact of climate change (e.g., precipitation and sea-level rise) on groundwater resources.
• Evaluate the potential of nature-based infrastructure in reducing the impacts of climate change at different scales.
• Develop machine learning-based surrogate models across scales for different purposes.
• Disseminate research findings using interactive notebooks.
• Publish research findings in peer-reviewed journals, and present at scientific meetings.

Additional Job Description

Minimum Qualifications:

• PhD in Civil and Environmental Engineering, hydrogeology, hydrology, or a related field.
• Strong background in numerical groundwater modeling particularly MODFLOW family.
• Experience in land-use and land-cover change with tools such as ArcGIS or QGIS.
• Programming skills such as Python, R, or MATLAB.

Preferred Qualifications:

Experience in or interest to learn:

• Integrated surface water - groundwater modeling
• Nature-based infrastructure
• Google Earth engine and GeeMap
• Machine learning models and surrogate modeling

Benefits:

• Competitive postdoctoral salary with benefits
• Access to state-of-the-art computational resources
• Contribute to impactful research that directly informs policy and benefits the community.

All employees are expected to:

• Promote a common purpose consistent with stated University goals and demonstrate a commitment to students and the learning environment.
• Possess the knowledge of general written standards and procedures utilized, and can read, interpret, and follow procedural and policy manual related to the job tasks.
• Demonstrate the ability to respond to supervision, guidance, and direction in a positive, receptive manner and in accordance with stated policies.
• Present a professional image in word, action, and attire.
• Apply effective techniques to create working relationships with others to achieve common goals; successfully communicates and collaborates with others to achieve goals.
• Demonstrate skills necessary to look at situations and processes critically to make recommendations for improvement.

The Division of Urologic Surgery in the Department of Surgery at Beth Israel Deaconess Medical Center and Harvard Medical School invites applications for a position at the level of Postdoctoral Scholar/Fellow in the laboratories of Drs. Aria Olumi and Zongwei Wang. The primary focus of this position is the exploration of novel pathways and mechanisms associated with steroid 5α-reductase inhibitors (5ARI) resistance in the context of benign prostatic hyperplasia (BPH) therapy, alongside the identification of clinically relevant epigenetic markers to enhance the efficacy of BPH management.

The candidate will spend the majority of their time performing research and is expected to present their work at laboratory meetings as well as departmental and scientific conferences in addition to publishing their findings.

The candidate is expected to perform essential experimental techniques including in vitro tissue culture, in vivo procedures involving rodent models, tissue harvesting and processing, molecular biology assays, and high-resolution confocal imaging.

Candidates with a background in cellular and molecular biology, urology research, and/or related disciplines are strongly encouraged to apply. Experience in the analysis of single cell RNA-sequencing and spatial transcriptomics data is advantageous, and proficiency in statistical analysis tools such as R or Python is desirable.

Interested candidates are invited to send CV accompanied by a paragraph on their background, training and research experience to Zongwei Wang (zwang12@bidmc.harvard.edu).

Requirements: MD or PhD or MD/PhD. Prior research experience and a proven publication record are imperative.

Atomic Lab (https://atomic-lab.org/) at the National Emerging Infectious Diseases Laboratories, Boston seeks a Postdoctoral Fellow with expertise in human immunology in infectious diseases and vaccinations. The successful candidate will spearhead a project focused on the subsets of memory CD8+ T cells, as a promising target for universal flu vaccine development. Ideally, the candidate must possess experience in using high-dimensional cytometry (CyTOF or Aurora, Cytek), multi-color panel design, immune cell sorting, and peptide/virus stimulation T-cell assays.

Responsibilities:

• Lead a project on memory T cells in vaccination and infections.
• Perform mass/spectral cytometry and ICS assays to evaluate the phenotype and functionality of memory T cells in blood and tissue samples from individuals after vaccination or during infection.
• Analyze mass/spectral cytometry data by FlowJo, Cytosplore or custom scripting in R/python.
• Use automated robotic platforms for various steps in cytometry.

Selection criteria

Essential:

• PhD in immunology, infection biology, or other closely related fields.
• Strong track record of productivity, as evidenced by first-author publications in peer-reviewed  journals.
• Proficiency in high-dimensional cytometry using CyTOF and Aurora, and cell sorting.
• Excellent communication skills, evidenced by oral presentations at internationally recognized conferences.
• Have specialist knowledge in infectious disease, human immunology, and immune memory.

Desirable:

• Acquisition of research funds through grant applications.
• Experience in supervising staff.

How to apply?

Please email the following documents to Prof. Adriana Tomic at atomic[at]bu.edu:

• CV
• List of publications with highlighted intellectual and technical contributions to each listed publication
• Cover letter detailing how you meet each selection criterion detailed in the job description
• Three letters of recommendation

Two exciting researcher positions are available in the Department of Computer Science at UiT The Arctic University of Norway .The positions are fixed term for a duration of three years, and are associated with the EU funded TRUSTING project. The research will be conducted within a thriving research group that has recently received grants of excellence. The main focus will be on voice and language-based AI for schizophrenia relapse detection

Appointment to the position of Postdoctoral Research Fellow is mainly intended to provide qualification for work in top academic positions. It is a prerequisite that the applicant can carry out the project over the full course of the employment period. No person may hold more than one fixed term position as a Postdoctoral Research Fellow at the same institution.

Goal: Contribute broadly to research on applications of AI in medicine, and in particular to the development and validation of novel computational language models, algorithms, and tools for spoken language-based detection of schizophrenia relapse in 6 different languages.

Start date: The workplace is at UiT in Tromsø. You must be able to start in the position in Tromsø, within six months after receiving the offer.

The position's field of research

The postdoctoral researcher positions are affiliated with ‘TRUSTING’, an EU funded research project where an international interdisciplinary team will develop a machine learning based monitoring system that leverages spoken language processing (SLP) and natural language processing (NLP) of speech recorded at home to calculate relapse risk. The developed monitoring system will be used in a randomized clinical trial, where the goal is to validate the clinical outcomes of those affected by schizophrenia. Within this project, we are seeking computer science researchers to take an active role in developing novel machine learning based systems and tools on the path towards clinical use and implementation of AI for the treatment and care of patients.

The candidates will contribute broadly to the project to enable the development of new algorithms for clinical AI based on patient data from heterogeneous sources, notably language/speech-based sources. The activity will focus on the development of a prototype implementation of early warning- and other AI-based decision support systems to study the effectiveness and safety of a novel clinical decision tool based on SLP/NLP, and utilizes large language models.

The project will focus on interaction with clinicians, with a goal of closing the gap between foundational research in machine learning and the clinical use of machine learning methods for the benefit of patients from a healthcare point of view. Hence, the work will be conducted in a highly interdisciplinary research environment. The candidates will collaborate with an international team consisting of clinicians, researchers in science and technology and health, industry partners, as well as personnel responsible for ICT, data security, privacy concerns and more. The UiT team will collaborate with the other research teams within the TRUSTING consortium.

The Health Data Lab (HDL) is a research group at the Department of Computer Science at UiT The Arctic University of Norway. HDL’s mission is to build and experimentally evaluate the systems, methods, and tools needed to analyze and interpret complex health datasets. In TRUSTING, the group collaborates with the Psychiatry Research Group at the Department of Clinical Medicine at UiT, where NLP methods are used to complement traditional methods of evaluating the mental state of psychiatric patients. The project will also work with The Norwegian centre for clinical artificial intelligence (SPKI) at the University Hospital of North Norway. In SPKI, the focus is patient-centered AI, in the sense that implementation and actual use of AI for the benefit of the patients and clinicians is considered to be equally important as the research activity of the SPKI centre.

All three research groups are in Tromsø, Norway. Our research groups work with the development of computer systems for data analysis, development of machine learning methods, and the clinical use of technology. Within the research group you will therefore work together with computer scientists with expertise in data management, distributed systems, security, machine learning, and development of health technology solutions. In addition, you will work with experts in psychology and psychiatry. The HDL and SPKI research groups are part of the Centre of Research-based Innovation SFI Visual Intelligence,  which is a center of excellence within machine learning research. The research groups are also active in entrepreneurship, clinical process innovation, and industry collaboration.

Contact

Further information about the position and UiT is available by contacting:

• Professor Brita Elvevåg: phone +47 91993063; email: brita.elvevag@uit.no
• Professor Lars Ailo Bongo: phone +47 92015508; email: lars.ailo.bongo@uit.no
• Associate Professor Karl Øyvind Mikalsen; phone +47 91565867; email: karl.o.mikalsen@uit.no

General and administrative questions:

• Head of administration Svein Tore Jensen, phone +47 77644036; email: svein.tore.jensen@uit.no

Qualifications

The positions require a PhD degree in computer science or a related field; a publication record that documents solid expertise in computer science, and strong technical skills. If you are at the final stages of your PhD, you may still apply if you have submitted your PhD thesis for evaluation within the application deadline. You must submit the thesis with your application. You must have received your PhD before the start-up date of the position.

We are looking for applicants with a strong interest and expertise in computer science research, with a focus on machine learning methods for the health domain, strong coding skills and familiarity with state-of-the-art machine learning frameworks. Previous experience in natural language processing, sound-based machine learning, development and deployment of health technology software is therefore considered beneficial. It is also beneficial if the applicant has an interest and previous experience in collaboration with inter-disciplinary or industrial collaborations. Candidates with research experience and relevant publications in conferences and journals will be considered with higher priority.

We are looking for interested, active and highly motivated candidates who like to explore new technologies, and who are independent thinkers but also team players who will enjoy collaborating with other researchers and clinicians. The positions are part of an interdisciplinary project, and close interaction with other project participants will be required. Good communication skills in English are necessary. Documented fluency in English is required. Nordic applicants can document their capabilities by attaching their high school diploma.

During this assessment process, emphasis will be placed on your potential for research as evidenced by your thesis and any other academic works. In addition, we may consider work experience or other activities of significance. The assessment will emphasize motivation and personal suitability for the position. The successful candidate has:

• Good collaboration skills
• Good communication and interaction with colleagues
• A desire to contribute towards a good working environment

At UiT we put emphasis on the quality, relevance and significance of the research work and not on where the work is published, in accordance with the principles of The San Francisco Declaration on Research Assessment (DORA). UiT wishes to increase the proportion of females in academic positions. In cases where two or more applicants are found to be approximately equally qualified, female applicants will be given priority.

Inclusion and diversity

UiT The Arctic University i Norway is working actively to promote equality, gender balance and diversity among employees and students, and to create an inclusive and safe working environment. We believe that inclusion and diversity is a strength, and we want employees with different competencies, professional experience, life experience and perspectives.

If you have a disability, a gap in your CV or immigrant background, we encourage you to tick the box for this in your application. If there are qualified applicants, we invite least one in each group for an interview. If you get the job, we will adapt the working conditions if you need it. Apart from selecting the right candidates, we will only use the information for anonymous statistics.

We offer

• Participation in an excellent and thriving research group that has recently received a prestigious ERC Synergy grant
• A productive, collaborative, and stimulating environment with researchers working on cutting-edge medical applications of artificial intelligence and speech technologies
• Good career opportunities
• A good academic environment with dedicated colleagues
• Flexible working hours and a state collective pay agreement
• Pension scheme through the state pension fund
• The possibility to balance professional development with a location to experience the liberating arctic nature: ski under the northern lights, hike and bike along the fjords

Norwegian health policy aims to ensure that everyone, irrespective of their personal finances and where they live, has access to good health and care services of equal standard. As an employee you will become member of the National Insurance Scheme which also include health care services.

More practical information for working and living in Norway can be found here: https://uit.no/staffmobility

Application

We will evaluate you based only on the documentation that you submit with the application. Your application must include:

• Application letter, including a 1-page summary of your motivation for applying for this position, why you are qualified for this position and how you will strengthen the research activity in the research team
• CV with complete overview of education, supervised professional training and professional experience.
• Documentation of English proficiency
• Contact information to 2-3 references
• Up to five academic works. The doctoral thesis is regarded as one work
• Description of your academic and software production and links to any open-source code.
• Description of your academic production, stating which works you consider most important and of relevance to this position. A brief description of the other listed works should also be included to demonstrate breadth of production. These descriptions shall be an attachment to the application.

All documentation to be considered must be in a Scandinavian language or English. We only accept applications and documentation sent via Jobbnorge within the application deadline.

Assessment

The applicants will be assessed by an expert committee. The committee's mandate is to undertake an assessment of the applicants' qualifications based on the written material presented by the applicants, and the detailed description draw up for the position.

The applicants who are assessed as best qualified will be called to an interview. The interview should among other things, aim to clarify the applicant’s motivation and personal suitability for the position. A trial lecture may also be held.

General information

The appointment is made in accordance with State regulations and guidelines at UiT. At our website, you will find more information for applicants.

The remuneration for Postdoctoral research fellow is in accordance with the State salary scale code 1352. A compulsory contribution of 2 % to the Norwegian Public Service Pension Fund will be deducted. You will become a member of the Norwegian Public Service Pension Fund, which gives you many benefits in addition to a lifelong pension: You may be entitled to financial support if you become ill or disabled, your family may be entitled to financial support when you die, you become insured against occupational injury or occupational disease, and you can get good terms on a mortgage. Read more about your employee benefits at: spk.no.

The successful candidate must be willing to get involved in the ongoing development of their department and the university as a whole.

UiT wishes to promote gender equality. If two or more applicants are found to be equally qualified, the university will rank applicants from the underrepresented gender ahead of others.

According to the Norwegian Freedom and Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.