Society for Conservation Biology
Overview
Harris-Stowe State University is a historically Black institution (HBCU) located in mid-town St. Louis, Missouri. Harris-Stowe's campus is near Gateway Arch, St. Louis Zoo, St. Louis Art and History Museums, Forest Park and other cultural and educational institutions. Harris-Stowe's diverse faculty and staff provide a wide range of academic programs to a culturally diverse student body in the St. Louis region. Job Summary
We are seeking a talented Data Scientist to analyze data from our research on the effects of light pollution on pregnancy. This is a limited-time position funded by a grant. The successful candidate will utilize advanced statistical and computational techniques to interpret complex datasets and contribute to the understanding of environmental impacts on reproductive health. Essential Functions
Strategic Leadership Train and organize undergraduate researchers. Collaborate with researchers to design experiments and analyze results. Present findings to the research team and at conferences. Stay abreast of industry trends, emerging technologies, and best practices in neurobiology and data science trends and technologies. Program Development and Management Analyze large datasets related to light pollution and pregnancy outcomes. Develop and implement data models and algorithms. Order supplies associated with the project data analyses. Lead the planning, design, and launch of new grant related protocols and procedures in line with industry standards. Quality Assurance Conduct experiments related to light pollution effects on pregnancy, under the guidance of senior researchers. Record, store, and manage experimental data accurately. Ensure compliance with safety and regulatory guidelines. Maintain a clean and organized lab environment. Faculty Support and Development Assist in the preparation of laboratory reports and presentations. Plan and execute Lab safety and procedure trainings. Provide guidance and support to senior faculty and undergraduate researchers in the development and delivery of all aspects of the grant. Visualize data findings through charts, graphs, and reports. Ensure data integrity and security Other duties as indicated by the PI of the grant. Minimum Education and Experience
Master's degree or higher in Data Science, Statistics, Computer Science, Neuroscience or a related field. Experience with statistical software (e.g., R, SAS, SPSS) and programming languages (e.g., Python, SQL). Strong analytical and problem-solving skills. Experience with data visualization tools (e.g., Tableau, Power BI). Excellent communication and teamwork skills. Prior neuroscience laboratory experience preferred. Strong attention to detail and organizational skills. Ability to work independently and as part of a team. Excellent communication skills. Preferred Qualifications
Master's degree or higher in Data Science, Statistics, Computer Science, Neuroscience or a related field. Knowledge, Skills and Abilities
Knowledge Neuroscience Fundamentals : Solid understanding of neurobiology, including brain anatomy, neural networks, electrophysiology, neurodevelopment, and neurodegenerative diseases. Familiarity with synaptic plasticity, brain mapping, and neural signaling pathways. Biological Data Types : In-depth knowledge of data types relevant to neurobiology (genomic, transcriptomic, proteomic, electrophysiological data); imaging data (MRI, fMRI, DTI); neural spike trains and behavioral datasets. Statistical Methods : Expertise in statistics, including linear models, Bayesian methods, hypothesis testing, and significance, applied to neuroscience data. Understanding how to handle biological variability and noise in data. Bioinformatics : Familiarity with analysis of high-throughput sequencing data, gene expression analysis, and protein-protein interaction networks relevant to neurobiology. Data Ethics and Security : Awareness of ethical considerations in handling sensitive biological data, data privacy regulations, and secure handling of medical and genetic data. Skills Programming : Strong programming skills in Python, R, MATLAB, and Julia; experience with TensorFlow, PyTorch, Pandas, SciPy, NumPy. Data Wrangling and Preprocessing : Clean, preprocess, and organize large datasets; handle missing data, normalize biological data, and prepare imaging data for analysis. Statistical Analysis : Advanced statistical techniques for biological datasets; experience with SPSS, SAS, or R for hypothesis testing, regression, and survival analysis. Data Visualization : Visualize complex data using Matplotlib, Plotly, Seaborn, ggplot2, or D3.js. Neuroimaging Analysis : Analyze MRI, fMRI, EEG data with FSL, SPM, AFNI, FreeSurfer, or BrainVoyager. Machine Learning Implementation : Implement ML algorithms for brain signal classification, image segmentation, neural decoding, and predictive models for neural activity. Algorithm Development : Develop custom algorithms for neurobiological applications. High-Performance Computing : Experience with AWS, Google Cloud, and HPC environments for large-scale datasets. Abilities Critical Thinking and Problem-Solving : Apply reasoning to interpret complex neurobiological data and identify patterns and potential causal relationships. Interdisciplinary Collaboration : Collaborate with scientists and researchers; communicate data science concepts to non-technical audiences. Data Interpretation : Interpret statistical analyses and ML model results in the context of neurobiology. Attention to Detail : Ensure data quality, integrity, and reproducibility. Curiosity and Innovation : Stay up-to-date and develop innovative approaches in neurobiology, ML, and computational neuroscience. Data Integration : Integrate diverse datasets into unified analyses. Visualization and Communication : Effectively visualize and communicate findings. Adaptability : Quickly learn new tools and methods. Other
Please No Phone Calls Due to high application volume, we are unable to accept phone calls or walk-in inquiries regarding applicant status. Only candidates selected for interviews will be contacted. EOE Statement Harris-Stowe State University is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, age, sex, sexual orientation, gender identity or expression, national origin, genetic information, disability, or protected veteran status. The above statements are intended to describe the general nature and level of work being performed and assigned for this position. This is not an exhaustive list, nor is it limited to all duties and responsibilities. HSSU reserves the right to amend and change responsibilities to meet business and organizational needs as necessary.
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Harris-Stowe State University is a historically Black institution (HBCU) located in mid-town St. Louis, Missouri. Harris-Stowe's campus is near Gateway Arch, St. Louis Zoo, St. Louis Art and History Museums, Forest Park and other cultural and educational institutions. Harris-Stowe's diverse faculty and staff provide a wide range of academic programs to a culturally diverse student body in the St. Louis region. Job Summary
We are seeking a talented Data Scientist to analyze data from our research on the effects of light pollution on pregnancy. This is a limited-time position funded by a grant. The successful candidate will utilize advanced statistical and computational techniques to interpret complex datasets and contribute to the understanding of environmental impacts on reproductive health. Essential Functions
Strategic Leadership Train and organize undergraduate researchers. Collaborate with researchers to design experiments and analyze results. Present findings to the research team and at conferences. Stay abreast of industry trends, emerging technologies, and best practices in neurobiology and data science trends and technologies. Program Development and Management Analyze large datasets related to light pollution and pregnancy outcomes. Develop and implement data models and algorithms. Order supplies associated with the project data analyses. Lead the planning, design, and launch of new grant related protocols and procedures in line with industry standards. Quality Assurance Conduct experiments related to light pollution effects on pregnancy, under the guidance of senior researchers. Record, store, and manage experimental data accurately. Ensure compliance with safety and regulatory guidelines. Maintain a clean and organized lab environment. Faculty Support and Development Assist in the preparation of laboratory reports and presentations. Plan and execute Lab safety and procedure trainings. Provide guidance and support to senior faculty and undergraduate researchers in the development and delivery of all aspects of the grant. Visualize data findings through charts, graphs, and reports. Ensure data integrity and security Other duties as indicated by the PI of the grant. Minimum Education and Experience
Master's degree or higher in Data Science, Statistics, Computer Science, Neuroscience or a related field. Experience with statistical software (e.g., R, SAS, SPSS) and programming languages (e.g., Python, SQL). Strong analytical and problem-solving skills. Experience with data visualization tools (e.g., Tableau, Power BI). Excellent communication and teamwork skills. Prior neuroscience laboratory experience preferred. Strong attention to detail and organizational skills. Ability to work independently and as part of a team. Excellent communication skills. Preferred Qualifications
Master's degree or higher in Data Science, Statistics, Computer Science, Neuroscience or a related field. Knowledge, Skills and Abilities
Knowledge Neuroscience Fundamentals : Solid understanding of neurobiology, including brain anatomy, neural networks, electrophysiology, neurodevelopment, and neurodegenerative diseases. Familiarity with synaptic plasticity, brain mapping, and neural signaling pathways. Biological Data Types : In-depth knowledge of data types relevant to neurobiology (genomic, transcriptomic, proteomic, electrophysiological data); imaging data (MRI, fMRI, DTI); neural spike trains and behavioral datasets. Statistical Methods : Expertise in statistics, including linear models, Bayesian methods, hypothesis testing, and significance, applied to neuroscience data. Understanding how to handle biological variability and noise in data. Bioinformatics : Familiarity with analysis of high-throughput sequencing data, gene expression analysis, and protein-protein interaction networks relevant to neurobiology. Data Ethics and Security : Awareness of ethical considerations in handling sensitive biological data, data privacy regulations, and secure handling of medical and genetic data. Skills Programming : Strong programming skills in Python, R, MATLAB, and Julia; experience with TensorFlow, PyTorch, Pandas, SciPy, NumPy. Data Wrangling and Preprocessing : Clean, preprocess, and organize large datasets; handle missing data, normalize biological data, and prepare imaging data for analysis. Statistical Analysis : Advanced statistical techniques for biological datasets; experience with SPSS, SAS, or R for hypothesis testing, regression, and survival analysis. Data Visualization : Visualize complex data using Matplotlib, Plotly, Seaborn, ggplot2, or D3.js. Neuroimaging Analysis : Analyze MRI, fMRI, EEG data with FSL, SPM, AFNI, FreeSurfer, or BrainVoyager. Machine Learning Implementation : Implement ML algorithms for brain signal classification, image segmentation, neural decoding, and predictive models for neural activity. Algorithm Development : Develop custom algorithms for neurobiological applications. High-Performance Computing : Experience with AWS, Google Cloud, and HPC environments for large-scale datasets. Abilities Critical Thinking and Problem-Solving : Apply reasoning to interpret complex neurobiological data and identify patterns and potential causal relationships. Interdisciplinary Collaboration : Collaborate with scientists and researchers; communicate data science concepts to non-technical audiences. Data Interpretation : Interpret statistical analyses and ML model results in the context of neurobiology. Attention to Detail : Ensure data quality, integrity, and reproducibility. Curiosity and Innovation : Stay up-to-date and develop innovative approaches in neurobiology, ML, and computational neuroscience. Data Integration : Integrate diverse datasets into unified analyses. Visualization and Communication : Effectively visualize and communicate findings. Adaptability : Quickly learn new tools and methods. Other
Please No Phone Calls Due to high application volume, we are unable to accept phone calls or walk-in inquiries regarding applicant status. Only candidates selected for interviews will be contacted. EOE Statement Harris-Stowe State University is an Equal Opportunity Employer. All qualified applicants will receive consideration without regard to race, color, religion, age, sex, sexual orientation, gender identity or expression, national origin, genetic information, disability, or protected veteran status. The above statements are intended to describe the general nature and level of work being performed and assigned for this position. This is not an exhaustive list, nor is it limited to all duties and responsibilities. HSSU reserves the right to amend and change responsibilities to meet business and organizational needs as necessary.
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