College of Science and Liberal Arts
Degree Overview
- Delivery Format: on-campus
- Required Credits:
Program Details
In the Biology of Health M.S. program, students will gain a strong foundation in those areas of biology most relevant to human health. The program’s objective is to prepare students to apply to health-related professional schools, including the taking of any required entrance exams such as the MCAT or DAT.
Graduates of the Biology of Health M.S. program will exhibit the following:
- Academic excellence: Our students will build the academic foundation for a successful career.
- Enhanced interpersonal and communication skills that result in the effective exchange of information.
- Honesty, integrity, and a commitment to abide by the principles of medical ethics.
What You Will Learn:
Alongside NJIT’s distinguished faculty, students of the M.S. Program in Biology of Health will enhance their biological understanding and analytical skills to become highly qualified candidates for professional schools.
Graduates from the M.S. Program in Biology of Health should all meet the following learning outcomes:
- Demonstrate biomedical science knowledge at the graduate level.
- Develop competencies with statistics, data analysis, and interpretation.
- Read and critically analyze scientific literature, and articulate its impact on biomedical sciences, medicine, public health, and society.
- Effectively communicate and present ideas to a variety of audiences.
- Demonstrate professionalism and technical expertise in the broad areas of observation, function, and social skills as related to effective health professionals.
Admissions & curriculum
Biology Salaries
Starting Salary, NJIT Average
Mid-Career Salary, National Average
A bachelor’s degree in biological or biomedical sciences is the fourth most popular degree option nationwide.
Where do Biology majors work?
- Clinical Research
- Optometric technician
- Equine Veterinary Assistant
- Pharmacy Technician
- Formulation Chemist
- Performance Physical Therapy And Sports Conditioning
- Princeton Orthopaedics
- Morristown Memorial Hospital
- L'Oreal USA
- Lansdale Rx Pharmacy
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I have built a strong foundation at NJIT to carry throughout my future endeavors."Neha Thati -
As a biology major, NJIT has opened up a world of possibilities and opportunities for me to pursue my goal of becoming a pharmacist. "Ines Nzameyo -
NJIT is preparing me to flourish in medical school and residency and become a strong and well-rounded professional."Chandni Patel
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Bucher, Dirk
- Professor
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Flammang, Brooke
- Associate Professor
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Fortune, Eric
- Associate Professor
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Golowasch, Jorge
- Professor and Research Director, Biological Sciences
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Nadim, Farzan
- Professor and Chair, Biological Sciences
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Rotstein, Horacio
- Professor
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Russell, Gareth
- Associate Professor, Associate Chair and Undergraduate Director, Biological Sciences
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Severi, Kristen
- Assistant Professor
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Soares, Daphne
- Associate Professor and MS Program Advisor, Biological Sciences
Contact Us
Need Help? We’re here to advise you.
Degree Overview
- Delivery Format: on-campus
- Required Credits:
Program Details
In the Data Science MS program, students will gain a strong, fundamental understanding of the statistical and computational tools of data analytics. They will build significant practical experience applying those skills to large and small data sets. These knowledge and experiential components of the program will enhance students’ career prospects in data science and related fields.
Graduates of the Data Science MS program will exhibit and engage in the following:
- Ethical & Professional Behavior: Students will develop skills to effectively communicate, collaborate in and lead teams, and act ethically in a professional setting.
- Academic Focus: Students work closely with their academic advisor to achieve their academic and career focus through selection of program electives
- Academic excellence: Students will build on their existing academic foundation, extending their pursuit of excellence in all program areas.
What You Will Learn:
Alongside NJIT’s distinguished faculty, students of the Data Science MS – Statistics Track program will develop and enhance their computational and analytical skills to become highly qualified professionals who can enter productive and in-demand
careers in New Jersey and throughout the U.S.
Graduates from the MS in the Data Science – Statistics Track program should all meet the following learning outcomes:
- Ability to use statistics and statistical methods to make inferences and draw conclusions from data.
- Ability to use advanced computing techniques to study data.
- Ability to identify well-defined features of quantifiable systems and extract useful inferences from data.
- Ability to formulate a mathematical model of a quantifiable system.
- Ability to distinguish between good models and bad models.
- Ability to communicate effectively.
- Ability to work effectively, both independently and as part of an interdisciplinary group.
- A recognition of the need for and an ability to engage in lifelong learning.
Admissions & curriculum
Data Science - Statistics Concentration Salaries
Starting Salary, NJIT Average
Mid-Career Salary, National Average
In late 2017, LinkedIn reported that Data Science and Machine Learning were the fastest growing job areas
Where do Data Science (Statistics Option) majors work?
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Getting a degree from a great school like NJIT gave me the opportunity to choose the job I wanted."Seif Issa -
NJIT was my dream school."Hilsson Angeles
Data Science (Statistics Option)
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Getting a degree from a great school like NJIT gave me the opportunity to choose the job I wanted."Seif Issa -
NJIT was my dream school."Hilsson Angeles
Related Majors
Degree Overview
- Delivery Format: on-campus
- Required Credits: 120
Program Details
In the Data Science B.S program, students will gain a strong, fundamental understanding of the statistical and computational tools of data analytics.
View our current Program and Courses [pdf]
The program’s objective is to prepare students for successful careers in data science and related fields or for graduate study.
Graduates of the Data Science B.S. program will exhibit and engage in the following:
- Ethical & Professional Behavior: Our students will develop skills to effectively communicate, lead and collaborate team dynamics and act ethically in a professional setting.
- Chosen Academic Focus: Students work closely with their academic advisor to achieve their academic and career focus through course selection of electives
- Academic excellence: Our students will build the academic foundation for a successful career.
What You Will Learn:
Alongside NJIT’s distinguished faculty, students of the Data Science B.S. – Statistics Track program will develop and enhance their computational and analytical skills to become highly qualified professionals who can enter productive and in-demand careers in New Jersey and throughout the U.S.
Graduates from the B.S. in the Data Science – Statistics Track program should all meet the following learning outcomes:
- Ability to use statistics and statistical methods to make inferences and draw conclusions from data.
- Ability to use advanced computing techniques to study data.
- Ability to identify well-defined features of quantifiable systems and extract useful inferences from data.
- Ability to formulate a mathematical model of a quantifiable system.
- Ability to distinguish between good model and bad models.
- Ability to communicate effectively.
- Ability to work effectively, both independently and as part of an interdisciplinary group.
- A recognition of the need for and an ability to engage in lifelong learning.
Admissions & curriculum
Data Science - Statistics Concentration Salaries
Starting Salary, NJIT Average
Mid-Career Salary, National Average
In late 2017, LinkedIn reported that Data Science and Machine Learning were the fastest growing job areas
Where do Data Science (Statistics Option) majors work?
-
NJIT was my dream school."Hilsson Angeles -
Getting a degree from a great school like NJIT gave me the opportunity to choose the job I wanted."Seif Issa
Degree Overview
- Delivery Format: on-campus
- Required Credits: 12
Program Details
In recent years, research into the myriad complexities of the brain and neurophysiology has gained momentum at NJIT across diverse disciplines, including biology, biomedical engineering, mathematical sciences and computing. With the formal inauguration of the university’s Institute for Brain and Neuroscience Research (IBNR) in 2017, the efforts of NJIT researchers to increase basic understanding of the brain that could lead to new healing therapies for related injuries and disease will be more sharply focused and closely coordinated.
What You Will Learn:
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Cellular Neurophysiology - The nervous system from a functional perspective. The goal is to understand how ion channels and other components of nerve cells give rise to electrical excitability and synaptic function, and how those properties are then used for coding information and higher order function in the nervous system.
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Systems Neuroscience - Neurophysical phenomena from a systems perspective. Basic concepts of cellular neuroscience, such as excitability, impulse conduction, and integration of activity at the cellular, before focusing on network level physiology of the nervous system and its role in the generation of behavior. The basic knowledge to understand neurobiological processes at all levels of complexity.
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Biological Imaging Techniques - A variety of approaches to examine biological structures at different microscopic scales: conventional light microscopy, fluorescent microscopy, modern high resolution light microscopy, and electron microscopy. Optical approaches to study the dynamics of cellular function, including calcium and voltage imaging, and molecular interactions.
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Neural Engineering - Understanding how the brain functions using engineering principles. Different instrumentation and signal processing algorithms to study how the brain functions, how to detect different pathologies and new applications for research. Basic overview of neurology, vector populations, neural networks, vision research, functional MRI, functional electrical stimulation, neural prosthetics, and other advanced research topics studying neurology.
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Medical Imaging Systems - Detailed introduction to medical imaging physics, instrumentation, data acquisition and image processing systems for reconstruction of multi-dimensional anatomical and functional medical images. Three-Dimensional medical imaging modalities including X-ray, Computer Tomography, Magnetic Resonance Imaging, Single Photon Emission Computer Tomography, Positron Emission Tomography, Ultrasound and optical imaging modalities are included.
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Approaches to Quantitative Analysis in the Life Sciences - Case studies of common data analytic methods used in the life sciences. The case studies are designed to help students who are interested in applications of statistical thinking to biological sciences appreciate the scope of quantitative methods, their underlying concepts, assumptions and limitations. While the mathematics of specific methods are not covered, students of the course will get and understanding of the diverse approaches to statistical inference in the life sciences.
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Intro to Comp Neuroscience - The modeling, computational and analysis techniques for single neurons and small neuronal networks. Knowledge of neurobiology, electric circuits and numerical tools for the solution of differential equations.
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Advanced Comp Neuroscience - Modeling and computational analysis of biological neuronal networks.
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Computational Systems Biology - Introduction to the mathematical and computational modeling of biological systems with a focus on chemical, biochemical, metabolic and genetic networks. Knowledge of biology and numerical tools for the solution of differential equations.
Admissions & curriculum
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Bucher, Dirk
- Professor
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Fortune, Eric
- Associate Professor
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Golowasch, Jorge
- Professor and Research Director, Biological Sciences
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Haspel, Gal
- Adjunct Instructor
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Nadim, Farzan
- Professor and Chair, Biological Sciences
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Severi, Kristen
- Assistant Professor
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Soares, Daphne
- Associate Professor and MS Program Advisor, Biological Sciences
Degree Overview
- Delivery Format: on-campus
- Required Credits: 12
Program Details
This hybrid program allows for individuals to learn from both a theoretical point of view as well as a practical one. Students will learn to develop sustainable solutions to environmental problems, preparing to work with regional, national and global communities to protect the environment and improve water quality. Jobs in this field are essential in planning, designing and constructing water and wastewater treatment plants, solid waste disposal systems, site remediation approaches and emission control measures.
What You Will Learn:
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Environmental Chemical Science - Principles of physical, inorganic and organic chemistry are applied to understanding the origins of environmental pollutants, their transport, distribution and decomposition pathways.
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Environmental Analysis - The analysis of environmental samples is studied from the acquisition of representative samples, through sample handling, chain of custody, sample storage, analytical method selection, analysis, and data treatment.
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Environmental Problem Solving - Solutions for current environmental problems. Students are asked to respond to an imaginary Request for Proposal (RFP) in writing and before a team of technical experts at an oral presentation. Solutions proposed in student RFPs must reflect knowledge of environmental science and technology in current use.
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Global Environmental Problems - Relationships of the earth's temperature balance, global air circulation patterns, global energy needs, and control and remediation technologies.
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Toxicology - The assessment of acute, sub-acute and chronic effects of hazardous and toxic chemicals. Qualitative and quantitative measures of toxicity and testing protocols are addressed. The role of toxicology in risk assessment and risk management is discussed.
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Environmental Microbiology - 1) basic microbiology: biochemical principles, cell structure organization, microbial nutrition and growth, 2) the important microbes involved in environmental microbiology and address the environments where they are found, and 3) how they are detected and monitored, and their effects on humans, and the environment.
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Energy and Sustainability - Energy fundamentals including the basic principles necessary to understand energy systems. The technological and engineered systems for processing and using different energy non-renewable and renewable sources. The social and environmental consequences of energy production, distribution, and use, including a comparison of socioeconomic models of global energy applications.
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Legal Aspects in Environmental Engineering - Control of air, water, and solid waste pollution by federal, state, and local government statutes and international law. Preparation of environmental impact statements and the right of private citizens to bring suit under federal clean air and water pollution legislation are discussed, as well as limitations on these rights.
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Sustainable Politics and Policy - Sustainability development and institutional efforts to implement strategies at various geopolitical scales: international, national, regional, and local. The course introduces tools to measure progress toward sustainability through the use of metrics such as ecological footprint analysis and life-cycle analysis.
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Physical Processes of Environmental Systems - Physical processes in various media (open water, porous media) under various hydraulic regimes (laminar and turbulent). Transport by diffusion, convection, and dispersion is considered along with absorption.
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Environmental Microbiology - Microbiology of natural and human impacted environment, fundamental microbiology in water treatment engineering, microbial detection methodologies, waterborne disease outbreaks, microbial risk assessment, biotechnologies for renewable energy, and other emerging topics
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Site Remediation - Regulations, cleanup standards, remedial investigations, feasibility studies, risk assessment, and safety. Established and innovative cleanup technologies such as incineration, containment, bioremediation, vapor extraction and ground water recovery.
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Physical and Chemical Treatment - Physical and chemical operations and processes employed in the treatment of water and wastewater. Gas transfer, coagulation, flocculation, solid-liquid separation, filtration, and disinfection.
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Biological Treatment - Principles of evaluation and control of water pollution that describe aerobic treatment processes such as oxidation ponds, trickling filters, and activated sludge; and anaerobic processes, and sludge handling and disposal as wall as biodegradability study techniques for various wastes.
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Environmental Impact Analysis - Environmental problems, federal and state standards, methodology for developing impact statements, case studies based on recent experience, basis for assessment and decision making.
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Stormwater Management - With an emphasis on design practices, you will learn regulatory framework, an overview of structural and non-structural BMPs, groundwater recharge analysis, estimate of runoff, and design of detention basin and drainage systems.
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Geotechnical Aspects of Solid Waste - municipal landfill, dredged materials, coal and incinerator ashes, identification and classification of waste materials, geological criteria for siting, laboratory and field testing, design for impoundment and isolation of waste, methods of stability analyses of landfill sites, techniques for stabilizing waste sites, leachate and gas collection and venting systems.
Admissions & curriculum
Degree Overview
- Delivery Format: on-campus
- Required Credits: 12
Program Details
Not only do these courses help students to earn credits toward a Master's Degree in Environmental Science at NJIT, but they enable students to quickly engage in research in this field. From this academic department, Distinguished Professor Dr. Somenath Mitra is one of NJIT's most decorated faculty after receiving the 2017 Benedetti Pichler Award following his research on carbon nanotube water filtration in the desalination process, earning NJIT a patent. Students in this program may be able to work with him directly.
What You Will Learn:
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Environmental Chemical Science - Principles of physical, inorganic and organic chemistry are applied to understanding the origins of environmental pollutants, their transport, distribution and decomposition pathways.
-
Environmental Analysis - The analysis of environmental samples is studied from the acquisition of representative samples, through sample handling, chain of custody, sample storage, analytical method selection, analysis, and data treatment.
-
Environmental Problem Solving - Solutions for current environmental problems. Students are asked to respond to an imaginary Request for Proposal (RFP) in writing and before a team of technical experts at an oral presentation. Solutions proposed in student RFPs must reflect knowledge of environmental science and technology in current use.
-
Global Environmental Problems - Relationships of the earth's temperature balance, global air circulation patterns, global energy needs, and control and remediation technologies.
-
Toxicology - The assessment of acute, sub-acute and chronic effects of hazardous and toxic chemicals. Qualitative and quantitative measures of toxicity and testing protocols are addressed. The role of toxicology in risk assessment and risk management is discussed.
-
Environmental Microbiology - 1) basic microbiology: biochemical principles, cell structure organization, microbial nutrition and growth, 2) the important microbes involved in environmental microbiology and address the environments where they are found, and 3) how they are detected and monitored, and their effects on humans, and the environment.
-
Energy and Sustainability - Energy fundamentals including the basic principles necessary to understand energy systems. The technological and engineered systems for processing and using different energy non-renewable and renewable sources. The social and environmental consequences of energy production, distribution, and use, including a comparison of socioeconomic models of global energy applications.
-
Legal Aspects in Environmental Engineering - Control of air, water, and solid waste pollution by federal, state, and local government statutes and international law. Preparation of environmental impact statements and the right of private citizens to bring suit under federal clean air and water pollution legislation are discussed, as well as limitations on these rights.
-
Sustainable Politics and Policy - Sustainability development and institutional efforts to implement strategies at various geopolitical scales: international, national, regional, and local. The course introduces tools to measure progress toward sustainability through the use of metrics such as ecological footprint analysis and life-cycle analysis.
Admissions & curriculum
Contact Us
Need Help? We’re here to advise you.
Degree Overview
- Delivery Format: on-campus
- Required Credits: 12
Program Details
The NJIT Department of Mathematics offers two types of courses: theoretical and practical. Graduates from this program will understand the concepts of advanced statistical techniques as well as modern day software that utilize these concepts.
What You Will Learn:
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Probability Distributions - Probability, conditional probability, random variables and distributions, independence, expectation, moment generating functions, useful parametric families of distributions, transformation of random variables, order statistics, sampling distributions under normality, the central limit theorem, convergence concepts and illustrative applications.
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Approaches to Quantitative Analysis in the Life Sciences - Case studies of common data analytic methods used in the life sciences. The case studies are designed to help students who are interested in applications of statistical thinking to biological sciences appreciate the scope of quantitative methods, their underlying concepts, assumptions and limitations.
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Clinical Trials Design and Analysis - Statistical methods and issues in the design of clinical trials and analysis of their data. Topic include clinical trial designs for phases 1-4, randomization principle and procedures, analysis of pharmacokinetic data for bioequivalence, multi-center trials, categorical data analysis, survival analysis, longitudinal data analysis, interim analysis, estimation of sample size and power, adjustment for multiplicity, evaluation of adverse events, and regulatory overview.
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Statistical Inference - Data reduction principles: sufficiency and likelihood. Theory and methods of point estimation and hypothesis testing, interval estimation, nonparametric tests, introduction to linear models.
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Sampling Theory - Role of sample surveys. Sampling from finite populations. Sampling designs, the Horowitz-Thompson estimator of the population mean. Different sampling methods, simple random sampling, stratified sampling, ratio and regression estimates, cluster sampling, systematic sampling.
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Design and Analysis of Experiments - Statistically designed experiments and their importance in data analysis, industrial experiments. Role of randomization. Fixed and random effect models and ANOVA, block design, latin square design, factorial and fractional factorial designs and their analysis.